hypothesis for sociology research paper

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Developing a Research Question

18 Hypotheses

When researchers do not have predictions about what they will find, they conduct research to answer a question or questions, with an open-minded desire to know about a topic, or to help develop hypotheses for later testing. In other situations, the purpose of research is to test a specific hypothesis or hypotheses. A hypothesis is a statement, sometimes but not always causal, describing a researcher’s expectations regarding anticipated finding. Often hypotheses are written to describe the expected relationship between two variables (though this is not a requirement). To develop a hypothesis, one needs to understand the differences between independent and dependent variables and between units of observation and units of analysis. Hypotheses are typically drawn from theories and usually describe how an independent variable is expected to affect some dependent variable or variables. Researchers following a deductive approach to their research will hypothesize about what they expect to find based on the theory or theories that frame their study. If the theory accurately reflects the phenomenon it is designed to explain, then the researcher’s hypotheses about what would be observed in the real world should bear out.

Sometimes researchers will hypothesize that a relationship will take a specific direction. As a result, an increase or decrease in one area might be said to cause an increase or decrease in another. For example, you might choose to study the relationship between age and legalization of marijuana. Perhaps you have done some reading in your spare time, or in another course you have taken. Based on the theories you have read, you hypothesize that “age is negatively related to support for marijuana legalization.” What have you just hypothesized? You have hypothesized that as people get older, the likelihood of their support for marijuana legalization decreases. Thus, as age moves in one direction (up), support for marijuana legalization moves in another direction (down). If writing hypotheses feels tricky, it is sometimes helpful to draw them out. and depict each of the two hypotheses we have just discussed.

Note that you will almost never hear researchers say that they have proven their hypotheses. A statement that bold implies that a relationship has been shown to exist with absolute certainty and that there is no chance that there are conditions under which the hypothesis would not bear out. Instead, researchers tend to say that their hypotheses have been supported (or not) . This more cautious way of discussing findings allows for the possibility that new evidence or new ways of examining a relationship will be discovered. Researchers may also discuss a null hypothesis, one that predicts no relationship between the variables being studied. If a researcher rejects the null hypothesis, he or she is saying that the variables in question are somehow related to one another.

Quantitative and qualitative researchers tend to take different approaches when it comes to hypotheses. In quantitative research, the goal often is to empirically test hypotheses generated from theory. With a qualitative approach, on the other hand, a researcher may begin with some vague expectations about what he or she will find, but the aim is not to test one’s expectations against some empirical observations. Instead, theory development or construction is the goal. Qualitative researchers may develop theories from which hypotheses can be drawn and quantitative researchers may then test those hypotheses. Both types of research are crucial to understanding our social world, and both play an important role in the matter of hypothesis development and testing. In the following section, we will look at qualitative and quantitative approaches to research, as well as mixed methods.

Text Attributions

This chapter has been adapted from Chapter 5.2 in Principles of Sociological Inquiry , which was adapted by the Saylor Academy without attribution to the original authors or publisher, as requested by the licensor. © Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License .

An Introduction to Research Methods in Sociology Copyright © 2019 by Valerie A. Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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2.1 Approaches to Sociological Research

Learning objectives.

By the end of this section, you should be able to:

Define and describe the scientific method.
Explain how the scientific method is used in sociological research.
Describe the function and importance of an interpretive framework.
Describe the differences in accuracy, reliability and validity in a research study.

When sociologists apply the sociological perspective and begin to ask questions, no topic is off limits. Every aspect of human behavior is a source of possible investigation. Sociologists question the world that humans have created and live in. They notice patterns of behavior as people move through that world. Using sociological methods and systematic research within the framework of the scientific method and a scholarly interpretive perspective, sociologists have discovered social patterns in the workplace that have transformed industries, in families that have enlightened family members, and in education that have aided structural changes in classrooms.

Sociologists often begin the research process by asking a question about how or why things happen in this world. It might be a unique question about a new trend or an old question about a common aspect of life. Once the question is formed, the sociologist proceeds through an in-depth process to answer it. In deciding how to design that process, the researcher may adopt a scientific approach or an interpretive framework. The following sections describe these approaches to knowledge.

The Scientific Method

Sociologists make use of tried and true methods of research, such as experiments, surveys, and field research. But humans and their social interactions are so diverse that these interactions can seem impossible to chart or explain. It might seem that science is about discoveries and chemical reactions or about proving ideas right or wrong rather than about exploring the nuances of human behavior.

However, this is exactly why scientific models work for studying human behavior. A scientific process of research establishes parameters that help make sure results are objective and accurate. Scientific methods provide limitations and boundaries that focus a study and organize its results.

The scientific method involves developing and testing theories about the social world based on empirical evidence. It is defined by its commitment to systematic observation of the empirical world and strives to be objective, critical, skeptical, and logical. It involves a series of six prescribed steps that have been established over centuries of scientific scholarship.

Sociological research does not reduce knowledge to right or wrong facts. Results of studies tend to provide people with insights they did not have before—explanations of human behaviors and social practices and access to knowledge of other cultures, rituals and beliefs, or trends and attitudes.

In general, sociologists tackle questions about the role of social characteristics in outcomes or results. For example, how do different communities fare in terms of psychological well-being, community cohesiveness, range of vocation, wealth, crime rates, and so on? Are communities functioning smoothly? Sociologists often look between the cracks to discover obstacles to meeting basic human needs. They might also study environmental influences and patterns of behavior that lead to crime, substance abuse, divorce, poverty, unplanned pregnancies, or illness. And, because sociological studies are not all focused on negative behaviors or challenging situations, social researchers might study vacation trends, healthy eating habits, neighborhood organizations, higher education patterns, games, parks, and exercise habits.

Sociologists can use the scientific method not only to collect but also to interpret and analyze data. They deliberately apply scientific logic and objectivity. They are interested in—but not attached to—the results. They work outside of their own political or social agendas. This does not mean researchers do not have their own personalities, complete with preferences and opinions. But sociologists deliberately use the scientific method to maintain as much objectivity, focus, and consistency as possible in collecting and analyzing data in research studies.

With its systematic approach, the scientific method has proven useful in shaping sociological studies. The scientific method provides a systematic, organized series of steps that help ensure objectivity and consistency in exploring a social problem. They provide the means for accuracy, reliability, and validity. In the end, the scientific method provides a shared basis for discussion and analysis (Merton 1963). Typically, the scientific method has 6 steps which are described below.

Step 1: Ask a Question or Find a Research Topic

The first step of the scientific method is to ask a question, select a problem, and identify the specific area of interest. The topic should be narrow enough to study within a geographic location and time frame. “Are societies capable of sustained happiness?” would be too vague. The question should also be broad enough to have universal merit. “What do personal hygiene habits reveal about the values of students at XYZ High School?” would be too narrow. Sociologists strive to frame questions that examine well-defined patterns and relationships.

In a hygiene study, for instance, hygiene could be defined as “personal habits to maintain physical appearance (as opposed to health),” and a researcher might ask, “How do differing personal hygiene habits reflect the cultural value placed on appearance?”

Step 2: Review the Literature/Research Existing Sources

To study crime, a researcher might also sort through existing data from the court system, police database, prison information, interviews with criminals, guards, wardens, etc. It’s important to examine this information in addition to existing research to determine how these resources might be used to fill holes in existing knowledge. Reviewing existing sources educates researchers and helps refine and improve a research study design.

Step 3: Formulate a Hypothesis

A hypothesis is an explanation for a phenomenon based on a conjecture about the relationship between the phenomenon and one or more causal factors. In sociology, the hypothesis will often predict how one form of human behavior influences another. For example, a hypothesis might be in the form of an “if, then statement.” Let’s relate this to our topic of crime: If unemployment increases, then the crime rate will increase.

In scientific research, we formulate hypotheses to include an independent variables (IV) , which are the cause of the change, and a dependent variable (DV) , which is the effect , or thing that is changed. In the example above, unemployment is the independent variable and the crime rate is the dependent variable.

In a sociological study, the researcher would establish one form of human behavior as the independent variable and observe the influence it has on a dependent variable. How does gender (the independent variable) affect rate of income (the dependent variable)? How does one’s religion (the independent variable) affect family size (the dependent variable)? How is social class (the dependent variable) affected by level of education (the independent variable)?

Taking an example from Table 12.1, a researcher might hypothesize that teaching children proper hygiene (the independent variable) will boost their sense of self-esteem (the dependent variable). Note, however, this hypothesis can also work the other way around. A sociologist might predict that increasing a child’s sense of self-esteem (the independent variable) will increase or improve habits of hygiene (now the dependent variable). Identifying the independent and dependent variables is very important. As the hygiene example shows, simply identifying related two topics or variables is not enough. Their prospective relationship must be part of the hypothesis.

Step 4: Design and Conduct a Study

Researchers design studies to maximize reliability , which refers to how likely research results are to be replicated if the study is reproduced. Reliability increases the likelihood that what happens to one person will happen to all people in a group or what will happen in one situation will happen in another. Cooking is a science. When you follow a recipe and measure ingredients with a cooking tool, such as a measuring cup, the same results is obtained as long as the cook follows the same recipe and uses the same type of tool. The measuring cup introduces accuracy into the process. If a person uses a less accurate tool, such as their hand, to measure ingredients rather than a cup, the same result may not be replicated. Accurate tools and methods increase reliability.

Researchers also strive for validity , which refers to how well the study measures what it was designed to measure. To produce reliable and valid results, sociologists develop an operational definition , that is, they define each concept, or variable, in terms of the physical or concrete steps it takes to objectively measure it. The operational definition identifies an observable condition of the concept. By operationalizing the concept, all researchers can collect data in a systematic or replicable manner. Moreover, researchers can determine whether the experiment or method validly represent the phenomenon they intended to study.

A study asking how tutoring improves grades, for instance, might define “tutoring” as “one-on-one assistance by an expert in the field, hired by an educational institution.” However, one researcher might define a “good” grade as a C or better, while another uses a B+ as a starting point for “good.” For the results to be replicated and gain acceptance within the broader scientific community, researchers would have to use a standard operational definition. These definitions set limits and establish cut-off points that ensure consistency and replicability in a study.

We will explore research methods in greater detail in the next section of this chapter.

Step 5: Draw Conclusions

After constructing the research design, sociologists collect, tabulate or categorize, and analyze data to formulate conclusions. If the analysis supports the hypothesis, researchers can discuss the implications of the results for the theory or policy solution that they were addressing. If the analysis does not support the hypothesis, researchers may consider repeating the experiment or think of ways to improve their procedure.

However, even when results contradict a sociologist’s prediction of a study’s outcome, these results still contribute to sociological understanding. Sociologists analyze general patterns in response to a study, but they are equally interested in exceptions to patterns. In a study of education, a researcher might predict that high school dropouts have a hard time finding rewarding careers. While many assume that the higher the education, the higher the salary and degree of career happiness, there are certainly exceptions. People with little education have had stunning careers, and people with advanced degrees have had trouble finding work. A sociologist prepares a hypothesis knowing that results may substantiate or contradict it.

Sociologists carefully keep in mind how operational definitions and research designs impact the results as they draw conclusions. Consider the concept of “increase of crime,” which might be defined as the percent increase in crime from last week to this week, as in the study of Swedish crime discussed above. Yet the data used to evaluate “increase of crime” might be limited by many factors: who commits the crime, where the crimes are committed, or what type of crime is committed. If the data is gathered for “crimes committed in Houston, Texas in zip code 77021,” then it may not be generalizable to crimes committed in rural areas outside of major cities like Houston. If data is collected about vandalism, it may not be generalizable to assault.

Step 6: Report Results

Researchers report their results at conferences and in academic journals. These results are then subjected to the scrutiny of other sociologists in the field. Before the conclusions of a study become widely accepted, the studies are often repeated in the same or different environments. In this way, sociological theories and knowledge develops as the relationships between social phenomenon are established in broader contexts and different circumstances.

Interpretive Framework

While many sociologists rely on empirical data and the scientific method as a research approach, others operate from an interpretive framework . While systematic, this approach doesn’t follow the hypothesis-testing model that seeks to find generalizable results. Instead, an interpretive framework, sometimes referred to as an interpretive perspective , seeks to understand social worlds from the point of view of participants, which leads to in-depth knowledge or understanding about the human experience.

Interpretive research is generally more descriptive or narrative in its findings. Rather than formulating a hypothesis and method for testing it, an interpretive researcher will develop approaches to explore the topic at hand that may involve a significant amount of direct observation or interaction with subjects including storytelling. This type of researcher learns through the process and sometimes adjusts the research methods or processes midway to optimize findings as they evolve.

Critical Sociology

Critical sociology focuses on deconstruction of existing sociological research and theory. Informed by the work of Karl Marx, scholars known collectively as the Frankfurt School proposed that social science, as much as any academic pursuit, is embedded in the system of power constituted by the set of class, caste, race, gender, and other relationships that exist in the society. Consequently, it cannot be treated as purely objective. Critical sociologists view theories, methods, and the conclusions as serving one of two purposes: they can either legitimate and rationalize systems of social power and oppression or liberate humans from inequality and restriction on human freedom. Deconstruction can involve data collection, but the analysis of this data is not empirical or positivist.

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The Craft of Writing a Strong Hypothesis

Writing a hypothesis is one of the essential elements of a scientific research paper. It needs to be to the point, clearly communicating what your research is trying to accomplish. A blurry, drawn-out, or complexly-structured hypothesis can confuse your readers. Or worse, the editor and peer reviewers.

A captivating hypothesis is not too intricate. This blog will take you through the process so that, by the end of it, you have a better idea of how to convey your research paper's intent in just one sentence.

What is a Hypothesis?

The first step in your scientific endeavor, a hypothesis, is a strong, concise statement that forms the basis of your research. It is not the same as a thesis statement , which is a brief summary of your research paper .

The sole purpose of a hypothesis is to predict your paper's findings, data, and conclusion. It comes from a place of curiosity and intuition . When you write a hypothesis, you're essentially making an educated guess based on scientific prejudices and evidence, which is further proven or disproven through the scientific method.

The reason for undertaking research is to observe a specific phenomenon. A hypothesis, therefore, lays out what the said phenomenon is. And it does so through two variables, an independent and dependent variable.

The independent variable is the cause behind the observation, while the dependent variable is the effect of the cause. A good example of this is “mixing red and blue forms purple.” In this hypothesis, mixing red and blue is the independent variable as you're combining the two colors at your own will. The formation of purple is the dependent variable as, in this case, it is conditional to the independent variable.

Different Types of Hypotheses‌

Types of hypotheses

Some would stand by the notion that there are only two types of hypotheses: a Null hypothesis and an Alternative hypothesis. While that may have some truth to it, it would be better to fully distinguish the most common forms as these terms come up so often, which might leave you out of context.

Apart from Null and Alternative, there are Complex, Simple, Directional, Non-Directional, Statistical, and Associative and casual hypotheses. They don't necessarily have to be exclusive, as one hypothesis can tick many boxes, but knowing the distinctions between them will make it easier for you to construct your own.

1. Null hypothesis

A null hypothesis proposes no relationship between two variables. Denoted by H 0 , it is a negative statement like “Attending physiotherapy sessions does not affect athletes' on-field performance.” Here, the author claims physiotherapy sessions have no effect on on-field performances. Even if there is, it's only a coincidence.

2. Alternative hypothesis

Considered to be the opposite of a null hypothesis, an alternative hypothesis is donated as H1 or Ha. It explicitly states that the dependent variable affects the independent variable. A good alternative hypothesis example is “Attending physiotherapy sessions improves athletes' on-field performance.” or “Water evaporates at 100 °C. ” The alternative hypothesis further branches into directional and non-directional.

Directional hypothesis: A hypothesis that states the result would be either positive or negative is called directional hypothesis. It accompanies H1 with either the ‘<' or ‘>' sign.
Non-directional hypothesis: A non-directional hypothesis only claims an effect on the dependent variable. It does not clarify whether the result would be positive or negative. The sign for a non-directional hypothesis is ‘≠.'

3. Simple hypothesis

A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, “Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking.

4. Complex hypothesis

In contrast to a simple hypothesis, a complex hypothesis implies the relationship between multiple independent and dependent variables. For instance, “Individuals who eat more fruits tend to have higher immunity, lesser cholesterol, and high metabolism.” The independent variable is eating more fruits, while the dependent variables are higher immunity, lesser cholesterol, and high metabolism.

5. Associative and casual hypothesis

Associative and casual hypotheses don't exhibit how many variables there will be. They define the relationship between the variables. In an associative hypothesis, changing any one variable, dependent or independent, affects others. In a casual hypothesis, the independent variable directly affects the dependent.

6. Empirical hypothesis

Also referred to as the working hypothesis, an empirical hypothesis claims a theory's validation via experiments and observation. This way, the statement appears justifiable and different from a wild guess.

Say, the hypothesis is “Women who take iron tablets face a lesser risk of anemia than those who take vitamin B12.” This is an example of an empirical hypothesis where the researcher the statement after assessing a group of women who take iron tablets and charting the findings.

7. Statistical hypothesis

The point of a statistical hypothesis is to test an already existing hypothesis by studying a population sample. Hypothesis like “44% of the Indian population belong in the age group of 22-27.” leverage evidence to prove or disprove a particular statement.

Characteristics of a Good Hypothesis

Writing a hypothesis is essential as it can make or break your research for you. That includes your chances of getting published in a journal. So when you're designing one, keep an eye out for these pointers:

A research hypothesis has to be simple yet clear to look justifiable enough.
It has to be testable — your research would be rendered pointless if too far-fetched into reality or limited by technology.
It has to be precise about the results —what you are trying to do and achieve through it should come out in your hypothesis.
A research hypothesis should be self-explanatory, leaving no doubt in the reader's mind.
If you are developing a relational hypothesis, you need to include the variables and establish an appropriate relationship among them.
A hypothesis must keep and reflect the scope for further investigations and experiments.

Separating a Hypothesis from a Prediction

Outside of academia, hypothesis and prediction are often used interchangeably. In research writing, this is not only confusing but also incorrect. And although a hypothesis and prediction are guesses at their core, there are many differences between them.

A hypothesis is an educated guess or even a testable prediction validated through research. It aims to analyze the gathered evidence and facts to define a relationship between variables and put forth a logical explanation behind the nature of events.

Predictions are assumptions or expected outcomes made without any backing evidence. They are more fictionally inclined regardless of where they originate from.

For this reason, a hypothesis holds much more weight than a prediction. It sticks to the scientific method rather than pure guesswork. "Planets revolve around the Sun." is an example of a hypothesis as it is previous knowledge and observed trends. Additionally, we can test it through the scientific method.

Whereas "COVID-19 will be eradicated by 2030." is a prediction. Even though it results from past trends, we can't prove or disprove it. So, the only way this gets validated is to wait and watch if COVID-19 cases end by 2030.

Finally, How to Write a Hypothesis

Quick tips on writing a hypothesis

1. Be clear about your research question

A hypothesis should instantly address the research question or the problem statement. To do so, you need to ask a question. Understand the constraints of your undertaken research topic and then formulate a simple and topic-centric problem. Only after that can you develop a hypothesis and further test for evidence.

2. Carry out a recce

Once you have your research's foundation laid out, it would be best to conduct preliminary research. Go through previous theories, academic papers, data, and experiments before you start curating your research hypothesis. It will give you an idea of your hypothesis's viability or originality.

Making use of references from relevant research papers helps draft a good research hypothesis. SciSpace Discover offers a repository of over 270 million research papers to browse through and gain a deeper understanding of related studies on a particular topic. Additionally, you can use SciSpace Copilot , your AI research assistant, for reading any lengthy research paper and getting a more summarized context of it. A hypothesis can be formed after evaluating many such summarized research papers. Copilot also offers explanations for theories and equations, explains paper in simplified version, allows you to highlight any text in the paper or clip math equations and tables and provides a deeper, clear understanding of what is being said. This can improve the hypothesis by helping you identify potential research gaps.

3. Create a 3-dimensional hypothesis

Variables are an essential part of any reasonable hypothesis. So, identify your independent and dependent variable(s) and form a correlation between them. The ideal way to do this is to write the hypothetical assumption in the ‘if-then' form. If you use this form, make sure that you state the predefined relationship between the variables.

In another way, you can choose to present your hypothesis as a comparison between two variables. Here, you must specify the difference you expect to observe in the results.

4. Write the first draft

Now that everything is in place, it's time to write your hypothesis. For starters, create the first draft. In this version, write what you expect to find from your research.

Clearly separate your independent and dependent variables and the link between them. Don't fixate on syntax at this stage. The goal is to ensure your hypothesis addresses the issue.

5. Proof your hypothesis

After preparing the first draft of your hypothesis, you need to inspect it thoroughly. It should tick all the boxes, like being concise, straightforward, relevant, and accurate. Your final hypothesis has to be well-structured as well.

Research projects are an exciting and crucial part of being a scholar. And once you have your research question, you need a great hypothesis to begin conducting research. Thus, knowing how to write a hypothesis is very important.

Now that you have a firmer grasp on what a good hypothesis constitutes, the different kinds there are, and what process to follow, you will find it much easier to write your hypothesis, which ultimately helps your research.

Now it's easier than ever to streamline your research workflow with SciSpace Discover . Its integrated, comprehensive end-to-end platform for research allows scholars to easily discover, write and publish their research and fosters collaboration.

It includes everything you need, including a repository of over 270 million research papers across disciplines, SEO-optimized summaries and public profiles to show your expertise and experience.

If you found these tips on writing a research hypothesis useful, head over to our blog on Statistical Hypothesis Testing to learn about the top researchers, papers, and institutions in this domain.

Frequently Asked Questions (FAQs)

1. what is the definition of hypothesis.

According to the Oxford dictionary, a hypothesis is defined as “An idea or explanation of something that is based on a few known facts, but that has not yet been proved to be true or correct”.

2. What is an example of hypothesis?

The hypothesis is a statement that proposes a relationship between two or more variables. An example: "If we increase the number of new users who join our platform by 25%, then we will see an increase in revenue."

3. What is an example of null hypothesis?

A null hypothesis is a statement that there is no relationship between two variables. The null hypothesis is written as H0. The null hypothesis states that there is no effect. For example, if you're studying whether or not a particular type of exercise increases strength, your null hypothesis will be "there is no difference in strength between people who exercise and people who don't."

4. What are the types of research?

• Fundamental research

• Applied research

• Qualitative research

• Quantitative research

• Mixed research

• Exploratory research

• Longitudinal research

• Cross-sectional research

• Field research

• Laboratory research

• Fixed research

• Flexible research

• Action research

• Policy research

• Classification research

• Comparative research

• Causal research

• Inductive research

• Deductive research

5. How to write a hypothesis?

• Your hypothesis should be able to predict the relationship and outcome.

• Avoid wordiness by keeping it simple and brief.

• Your hypothesis should contain observable and testable outcomes.

• Your hypothesis should be relevant to the research question.

6. What are the 2 types of hypothesis?

• Null hypotheses are used to test the claim that "there is no difference between two groups of data".

• Alternative hypotheses test the claim that "there is a difference between two data groups".

7. Difference between research question and research hypothesis?

A research question is a broad, open-ended question you will try to answer through your research. A hypothesis is a statement based on prior research or theory that you expect to be true due to your study. Example - Research question: What are the factors that influence the adoption of the new technology? Research hypothesis: There is a positive relationship between age, education and income level with the adoption of the new technology.

8. What is plural for hypothesis?

The plural of hypothesis is hypotheses. Here's an example of how it would be used in a statement, "Numerous well-considered hypotheses are presented in this part, and they are supported by tables and figures that are well-illustrated."

9. What is the red queen hypothesis?

The red queen hypothesis in evolutionary biology states that species must constantly evolve to avoid extinction because if they don't, they will be outcompeted by other species that are evolving. Leigh Van Valen first proposed it in 1973; since then, it has been tested and substantiated many times.

10. Who is known as the father of null hypothesis?

The father of the null hypothesis is Sir Ronald Fisher. He published a paper in 1925 that introduced the concept of null hypothesis testing, and he was also the first to use the term itself.

11. When to reject null hypothesis?

You need to find a significant difference between your two populations to reject the null hypothesis. You can determine that by running statistical tests such as an independent sample t-test or a dependent sample t-test. You should reject the null hypothesis if the p-value is less than 0.05.

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Hypothesis: Functions, Problems, Types, Characteristics, Examples

Basic Elements of the Scientific Method: Hypotheses

The Function of the Hypotheses

A hypothesis states what one is looking for in an experiment. When facts are assembled, ordered, and seen in a relationship, they build up to become a theory. This theory needs to be deduced for further confirmation of the facts, this formulation of the deductions constitutes of a hypothesis. As a theory states a logical relationship between facts and from this, the propositions which are deduced should be true. Hence, these deduced prepositions are called hypotheses.

Problems in Formulating the Hypothesis

As difficult as the process may be, it is very essential to understand the need of a hypothesis. The research would be much unfocused and a random empirical wandering without it. The hypothesis provides a necessary link between the theory and investigation which often leads to the discovery of additions to knowledge.

There are three major difficulties in the formulation of a hypothesis, they are as follows:

Absence of a clear theoretical framework
Lack of ability to utilize that theoretical framework logically
Failure to be acquainted with available research techniques so as to phrase the hypothesis properly.

Sometimes the deduction of a hypothesis may be difficult as there would be many variables and the necessity to take them all into consideration becomes a challenge. For instance, observing two cases:

Principle: A socially recognized relationship with built-in strains also governed by the institutional controls has to ensure conformity of the participants with implicit or explicit norms.

Deduction: This situation holds much more sense to the people who are in professions such as psychotherapy, psychiatry and law to some extent. They possess a very intimate relationship with their clients, thus are more susceptible to issues regarding emotional strains in the client-practitioner relationship and more implicit and explicit controls over both participants in comparison to other professions.

The above-mentioned case has variable hypotheses, so the need is to break them down into sub hypotheses, they are as follows:

Specification of the degree of difference
Specification of profession and problem
Specification of kinds of controls.

2. Principle: Extensive but relatively systematized data show the correlation between members of the upper occupational class and less unhappiness and worry. Also, they are subjected to more formal controls than members of the lower strata.

Deduction: There can numerous ways to approach this principle, one could go with the comparison applying to martial relationships of the members and further argue that such differential pressures could be observed through divorce rates. This hypothesis would show inverse correlations between class position and divorce rates. There would be a very strong need to define the terms carefully to show the deduction from the principle problem.

The reference of these examples showcases a major issue in the hypothesis formulations procedures. One needs to keep the lines set for the deductions and one should be focusing on having a hypothesis at the beginning of the experiment, that hypothesis may be subject to change in the later stages and it is referred to as a „working hypothesis. Hence, the devising and utilization of a hypothesis is essential for the success of the experiment.

Types of Hypothesis

There are many ways to classify hypotheses, but it seems adequate to distinguish to separate them on the basis of their level of abstraction. They can be divided into three broad levels which will be increasing in abstractness.

The existence of empirical uniformities : These hypotheses are made from problems which usually have a very high percentage of representing scientific examination of common–sense proportions. These studies may show a variety of things such as the distribution of business establishments in a city, behavior patterns of specific groups, etc. and they tend to show no irregularities in their data collection or review. There have been arguments which say that these aren’t hypothesis as they represent what everyone knows. This can be counter argued on the basis of two things that, “what everyone knows” isn’t always in coherence with the framework of science and it may also be incorrect. Hence, testing these hypotheses is necessary too.
Complex ideal types: These hypotheses aim at testing the existence of logically derived relationships between empirical uniformities. This can be understood with an example, to observe ecology one should take in many factors and see the relationship between and how they affect the greater issue. A theory by Ernest W. Burgess gave out the statement that concentric growth circles are the one which characterize the city. Hence, all issues such as land values, industrial growth, ethnic groups, etc. are needed to be analyzed for forming a correct and reasonable hypothesis.
Relations of analytic variables: These hypotheses are a bit more complex as they focus on they lead to the formulation of a relationship between the changes in one property with respect to another. For instance, taking the example of human fertility in diverse regions, religions, wealth gap, etc. may not always affect the end result but it doesn’t mean that the variables need not be accounted for. This level of hypothesizing is one of the most effective and sophisticated and thus is only limited by theory itself.

Science and Hypothesis

“The general culture in which a science develops furnishes many of its basic hypotheses” holds true as science has developed more in the West and is no accident that it is a function of culture itself. This is quite evident with the culture of the West as they read for morals, science and happiness. After the examination of a bunch of variables, it is quite easy to say that the cultural emphasis upon happiness has been productive of an almost limitless range.

The hypotheses originate from science; a key example in the form of “socialization” may be taken. The socialization process in learning science involves a feedback mechanism between the scientist and the student. The student learns from the scientist and then tests for results with his own experience, and the scientist in turn has to do the same with his colleagues.

Analogies are a source of useful hypotheses but not without its dangers as all variables may not be accounted for it as no civilization has a perfect system.

Hypotheses are also the consequence of personal, idiosyncratic experience as the manner in which the individual reacts to the hypotheses is also important and should be accounted for in the experiment.

The Characteristics for Usable Hypotheses

The criteria for judging a hypothesis as mentioned below:

Complete Clarity : A good hypothesis should have two main elements, the concepts should be clearly defined and they should be definitions which are communicable and accepted by a larger section of the public. A lot of sources may be used and fellow associates may be used to help with the cause.
Empirical Referents : A great hypothesis should have scientific concepts with the ultimate empirical referent. It can‟t be based on moral judgment though it can explore them but the goal should be separated from moral preachment and the acceptance of values. A good start could be analyzing the concepts which express attitudes rather than describing or referring to empirical phenomena.
Specific Goal : The goal and procedure of the hypothesis should be tangible as grand experiments are harder to carry out. All operations and predictions should be mapped and in turn the possibility of testing the hypothesis increases. This not only enables the conceptual clarity but also the description of any indexes used. These indexes are used as variables for testing hypotheses on a larger scale. A general prediction isn’t as reliable as a specific prediction as the specific prediction provides a better result.
Relation to Available Techniques : The technique with which a hypothesis is tested is of the utmost importance and so thorough research should be carried out before the experiment in order to find the best possible way to go about it. The example of Karl Marx may be given regarding his renowned theories; he formulated his hypothesis by observing individuals and thus proving his hypothesis. So, finding the right technique may be the key to a successful test.
Relation to a Body of Theory: Theories on social relations can never be developed in isolation but they are a further extension of already developed or developing theories. For instance, if the “intelligence quotient” of a member of the society is to be measured, certain variables such as caste, ethnicity, nationality, etc. are chosen thus deductions are made from time to time to eventually find out what is the factor that influences intelligence.

The Conclusion

The formulation of a hypothesis is probably the most necessary step in good research practice and it is very essential to get the thought process started. It helps the researcher to have a specific goal in mind and deduce the end result of an experiment with ease and efficiency. History is evident that asking the right questions always works out fine.

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How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

An independent variable is something the researcher changes or controls.
A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

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Step 1. Ask a question

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

The relevant variables
The specific group being studied
The predicted outcome of the experiment or analysis

5. Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

Sampling methods
Simple random sampling
Stratified sampling
Cluster sampling
Likert scales
Reproducibility

Statistics

Null hypothesis
Statistical power
Probability distribution
Effect size
Poisson distribution

Research bias

Optimism bias
Cognitive bias
Implicit bias
Hawthorne effect
Anchoring bias
Explicit bias

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A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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2.3: Propositions and Hypotheses

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Page ID 26213

Anol Bhattacherjee
University of South Florida via Global Text Project

Figure 2.2 shows how theoretical constructs such as intelligence, effort, academic achievement, and earning potential are related to each other in a nomological network. Each of these relationships is called a proposition. In seeking explanations to a given phenomenon or behavior, it is not adequate just to identify key concepts and constructs underlying the target phenomenon or behavior. We must also identify and state patterns of relationships between these constructs. Such patterns of relationships are called propositions. A proposition is a tentative and conjectural relationship between constructs that is stated in a declarative form. An example of a proposition is: “An increase in student intelligence causes an increase in their academic achievement.” This declarative statement does not have to be true, but must be empirically testable using data, so that we can judge whether it is true or false. Propositions are generally derived based on logic (deduction) or empirical observations (induction).

Because propositions are associations between abstract constructs, they cannot be tested directly. Instead, they are tested indirectly by examining the relationship between corresponding measures (variables) of those constructs. The empirical formulation of propositions, stated as relationships between variables, is called hypotheses (see Figure 2.1). Since IQ scores and grade point average are operational measures of intelligence and academic achievement respectively, the above proposition can be specified in form of the hypothesis: “An increase in students’ IQ score causes an increase in their grade point average.” Propositions are specified in the theoretical plane, while hypotheses are specified in the empirical plane. Hence, hypotheses are empirically testable using observed data, and may be rejected if not supported by empirical observations. Of course, the goal of hypothesis testing is to infer whether the corresponding proposition is valid.

Hypotheses can be strong or weak. “Students’ IQ scores are related to their academic achievement” is an example of a weak hypothesis, since it indicates neither the directionality of the hypothesis (i.e., whether the relationship is positive or negative), nor its causality (i.e., whether intelligence causes academic achievement or academic achievement causes intelligence). A stronger hypothesis is “students’ IQ scores are positively related to their academic achievement”, which indicates the directionality but not the causality. A still better hypothesis is “students’ IQ scores have positive effects on their academic achievement”, which specifies both the directionality and the causality (i.e., intelligence causes academic achievement, and not the reverse). The signs in Figure 2.2 indicate the directionality of the respective hypotheses.

Also note that scientific hypotheses should clearly specify independent and dependent variables. In the hypothesis, “students’ IQ scores have positive effects on their academic achievement,” it is clear that intelligence is the independent variable (the “cause”) and academic achievement is the dependent variable (the “effect”). Further, it is also clear that this hypothesis can be evaluated as either true (if higher intelligence leads to higher academic achievement) or false (if higher intelligence has no effect on or leads to lower academic achievement). Later on in this book, we will examine how to empirically test such cause-effect relationships. Statements such as “students are generally intelligent” or “all students can achieve academic success” are not scientific hypotheses because they do not specify independent and dependent variables, nor do they specify a directional relationship that can be evaluated as true or false.

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Chapter 2. Sociological Research

Learning objectives.

2.1. Approaches to Sociological Research

Define and describe the scientific method
Explain how the scientific method is used in sociological research
Understand the difference between positivist and interpretive approaches to the scientific method in sociology
Define what reliability and validity mean in a research study

2.2. Research Methods

Differentiate between four kinds of research methods: surveys, experiments, field research, and secondary data and textual analysis
Understand why different topics are better suited to different research approaches

2.3. Ethical Concerns

Understand why ethical standards exist
Demonstrate awareness of the Canadian Sociological Association’s Code of Ethics
Define value neutrality
Outline some of the issues of value neutrality in sociology

Introduction to Sociological Research

In the university cafeteria, you set your lunch tray down at a table, grab a chair, join a group of your classmates, and hear the start of two discussions. One person says, “It’s weird how Justin Bieber has 48 million followers on Twitter.” Another says, “Disney World is packed year round.” Those two seemingly benign statements are claims, or opinions, based on everyday observation of human behaviour. Perhaps the speakers had firsthand experience, talked to experts, conducted online research, or saw news segments on TV. In response, two conversations erupt. “I don’t see why anyone would want to go to Disney World and stand in those long lines.” “Are you kidding?! Going to Disney World is one of my favourite childhood memories.” “It’s the opposite for me with Justin Bieber. Seeing people camp out outside his hotel just to get a glimpse of him; it doesn’t make sense.” “Well, you’re not a teenage girl.” “Going to a theme park is way different than trying to see a teenage heart throb.” “But both are things people do for the same reason: they’re looking for a good time.” “If you call getting crushed by a crowd of strangers fun.”

As your classmates at the lunch table discuss what they know or believe, the two topics converge. The conversation becomes a debate. Someone compares Beliebers to Beatles fans. Someone else compares Disney World to a cruise. Students take sides, agreeing or disagreeing, as the conversation veers to topics such as crowd control, mob mentality, political protests, and group dynamics. If you contributed your expanding knowledge of sociological research to this conversation, you might make statements like these: “Justin Bieber’s fans long for an escape from the boredom of real teenage life. Beliebers join together claiming they want romance, except what they really want is a safe place to explore the confusion of teenage sexual feelings.” And this: “Mickey Mouse is a larger-than-life cartoon celebrity. Disney World is a place where families go to see what it would be like to live inside a cartoon.” You finish lunch, clear away your tray, and hurry to your next class. But you are thinking of Justin Bieber and Disney World. You have a new perspective on human behaviour and a list of questions that you want answered. That is the purpose of sociological research—to investigate and provide insights into how human societies function.

Although claims and opinions are part of sociology, sociologists use empirical evidence (that is, evidence corroborated by direct experience and/or observation) combined with the scientific method or an interpretive framework to deliver sound sociological research. They also rely on a theoretical foundation that provides an interpretive perspective through which they can make sense of scientific results. A truly scientific sociological study of the social situations up for discussion in the cafeteria would involve these prescribed steps: defining a specific question, gathering information and resources through observation, forming a hypothesis, testing the hypothesis in a reproducible manner, analyzing and drawing conclusions from the data, publishing the results, and anticipating further development when future researchers respond to and retest findings.

An appropriate starting point in this case might be the question “What do fans of Justin Bieber seek that drives them to follow his Twitter comments so faithfully?” As you begin to think like a sociologist, you may notice that you have tapped into your observation skills. You might assume that your observations and insights are valuable and accurate. But the results of casual observation are limited by the fact that there is no standardization—who is to say one person’s observation of an event is any more accurate than another’s? To mediate these concerns, sociologists rely on systematic research processes.

When sociologists apply the sociological perspective and begin to ask questions, no topic is off limits. Every aspect of human behaviour is a source of possible investigation. Sociologists question the world that humans have created and live in. They notice patterns of behaviour as people move through that world. Using sociological methods and systematic research within the framework of the scientific method and a scholarly interpretive perspective, sociologists have discovered workplace patterns that have transformed industries, family patterns that have enlightened parents, and education patterns that have aided structural changes in classrooms. The students at that university cafeteria discussion put forth a few loosely stated opinions.

If the human behaviours around those claims were tested systematically, a student could write a report and offer the findings to fellow sociologists and the world in general. The new perspective could help people understand themselves and their neighbours and help people make better decisions about their lives. It might seem strange to use scientific practices to study social trends, but, as we shall see, it’s extremely helpful to rely on systematic approaches that research methods provide. Sociologists often begin the research process by asking a question about how or why things happen in this world. It might be a unique question about a new trend or an old question about a common aspect of life. Once a question is formed, a sociologist proceeds through an in-depth process to answer it. In deciding how to design that process, the researcher may adopt a positivist approach or an interpretive approach. The following sections describe these approaches to knowledge.

The Scientific Method

Sociologists make use of tried-and-true methods of research, such as experiments, surveys, field research, and textual analysis. But humans and their social interactions are so diverse that they can seem impossible to chart or explain. It might seem that science is about discoveries and chemical reactions or about proving ideas right or wrong rather than about exploring the nuances of human behaviour. However, this is exactly why scientific models work for studying human behaviour. A scientific process of research establishes parameters that help make sure results are objective and accurate. Scientific methods provide limitations and boundaries that focus a study and organize its results. This is the case for both positivist or quantitative methodologies and interpretive or qualitative methodologies. The scientific method involves developing and testing theories about the world based on empirical evidence. It is defined by its commitment to systematic observation of the empirical world and strives to be objective, critical, skeptical, and logical. It involves a series of prescribed steps that have been established over centuries of scholarship.

But just because sociological studies use scientific methods does not make the results less human. Sociological topics are not reduced to right or wrong facts. In this field, results of studies tend to provide people with access to knowledge they did not have before—knowledge of other cultures, knowledge of rituals and beliefs, knowledge of trends and attitudes. No matter what research approach is used, researchers want to maximize the study’s reliability (how likely research results are to be replicated if the study is reproduced). Reliability increases the likelihood that what is true of one person will be true of all people in a group. Researchers also strive for validity (how well the study measures what it was designed to measure).

Returning to the Disney World topic, reliability of a study would reflect how well the resulting experience represents the average experience of theme park-goers. Validity would ensure that the study’s design accurately examined what it was designed to study, so an exploration of adults’ interactions with costumed mascots should address that issue and not veer into other age groups’ interactions with them or into adult interactions with staff or other guests.

In general, sociologists tackle questions about the role of social characteristics in outcomes. For example, how do different communities fare in terms of psychological well-being, community cohesiveness, range of vocation, wealth, crime rates, and so on? Are communities functioning smoothly? Sociologists look between the cracks to discover obstacles to meeting basic human needs. They might study environmental influences and patterns of behaviour that lead to crime, substance abuse, divorce, poverty, unplanned pregnancies, or illness. And, because sociological studies are not all focused on problematic behaviours or challenging situations, researchers might study vacation trends, healthy eating habits, neighbourhood organizations, higher education patterns, games, parks, and exercise habits.

Sociologists can use the scientific method not only to collect but to interpret and analyze the data. They deliberately apply scientific logic and objectivity. They are interested in but not attached to the results. Their research work is independent of their own political or social beliefs. This does not mean researchers are not critical. Nor does it mean they do not have their own personalities, complete with preferences and opinions. But sociologists deliberately use the scientific method to maintain as much objectivity, focus, and consistency as possible in a particular study. With its systematic approach, the scientific method has proven useful in shaping sociological studies. The scientific method provides a systematic, organized series of steps that help ensure objectivity and consistency in exploring a social problem. They provide the means for accuracy, reliability, and validity. In the end, the scientific method provides a shared basis for discussion and analysis (Merton 1963). Typically, the scientific method starts with these steps—1) ask a question, 2) research existing sources, 3) formulate a hypothesis—described below.

Ask a Question

The first step of the scientific method is to ask a question, describe a problem, and identify the specific area of interest. The topic should be narrow enough to study within a geography and timeframe. “Are societies capable of sustained happiness?” would be too vague. The question should also be broad enough to have universal merit. “What do personal hygiene habits reveal about the values of students at XYZ High School?” would be too narrow. That said, happiness and hygiene are worthy topics to study.

Sociologists do not rule out any topic, but would strive to frame these questions in better research terms. That is why sociologists are careful to define their terms. In a hygiene study, for instance, hygiene could be defined as “personal habits to maintain physical appearance (as opposed to health),” and a researcher might ask, “How do differing personal hygiene habits reflect the cultural value placed on appearance?” When forming these basic research questions, sociologists develop an operational definition ; that is, they define the concept in terms of the physical or concrete steps it takes to objectively measure it. The concept is translated into an observable variable , a measure that has different values. The operational definition identifies an observable condition of the concept.

By operationalizing a variable of the concept, all researchers can collect data in a systematic or replicable manner. The operational definition must be valid in the sense that it is an appropriate and meaningful measure of the concept being studied. It must also be reliable, meaning that results will be close to uniform when tested on more than one person. For example, “good drivers” might be defined in many ways: those who use their turn signals, those who don’t speed, or those who courteously allow others to merge. But these driving behaviours could be interpreted differently by different researchers and could be difficult to measure. Alternatively, “a driver who has never received a traffic violation” is a specific description that will lead researchers to obtain the same information, so it is an effective operational definition.

Research Existing Sources

The next step researchers undertake is to conduct background research through a literature review , which is a review of any existing similar or related studies. A visit to the library and a thorough online search will uncover existing research about the topic of study. This step helps researchers gain a broad understanding of work previously conducted on the topic at hand and enables them to position their own research to build on prior knowledge. It allows them to sharpen the focus of their research question and avoid duplicating previous research. Researchers—including student researchers—are responsible for correctly citing existing sources they use in a study or that inform their work. While it is fine to build on previously published material (as long as it enhances a unique viewpoint), it must be referenced properly and never plagiarized. To study hygiene and its value in a particular society, a researcher might sort through existing research and unearth studies about childrearing, vanity, obsessive-compulsive behaviours, and cultural attitudes toward beauty. It’s important to sift through this information and determine what is relevant. Using existing sources educates a researcher and helps refine and improve a study’s design.

Formulate a Hypothesis

A hypothesis is an assumption about how two or more variables are related; it makes a conjectural statement about the relationship between those variables. It is an “educated guess” because it is not random but based on theory, observations, patterns of experience, or the existing literature. The hypothesis formulates this guess in the form of a testable proposition. However, how the hypothesis is handled differs between the positivist and interpretive approaches. Positivist methodologies are often referred to as hypothetico-deductive methodologies . A hypothesis is derived from a theoretical proposition. On the basis of the hypothesis a prediction or generalization is logically deduced. In positivist sociology, the hypothesis predicts how one form of human behaviour influences another.

Successful prediction will determine the adequacy of the hypothesis and thereby test the theoretical proposition. Typically positivist approaches operationalize variables as quantitative data ; that is, by translating a social phenomenon like “health” into a quantifiable or numerically measurable variable like “number of visits to the hospital.” This permits sociologists to formulate their predictions using mathematical language like regression formulas, to present research findings in graphs and tables, and to perform mathematical or statistical techniques to demonstrate the validity of relationships.

Variables are examined to see if there is a correlation between them. When a change in one variable coincides with a change in another variable there is a correlation. This does not necessarily indicate that changes in one variable causes a change in another variable, however, just that they are associated. A key distinction here is between independent and dependent variables. In research, independent variables are the cause of the change. The dependent variable is the effect , or thing that is changed. For example, in a basic study, the researcher would establish one form of human behaviour as the independent variable and observe the influence it has on a dependent variable. How does gender (the independent variable) affect rate of income (the dependent variable)? How does one’s religion (the independent variable) affect family size (the dependent variable)? How is social class (the dependent variable) affected by level of education (the independent variable)? For it to become possible to speak about causation, three criteria must be satisfied:

There must be a relationship or correlation between the independent and dependent variables.
The independent variable must be prior to the dependent variable.
There must be no other intervening variable responsible for the causal relationship.

Table 2.1. Examples of Dependent and Independent Variables Typically, the independent variable causes the dependent variable to change in some way.

At this point, a researcher’s operational definitions help measure the variables. In a study asking how tutoring improves grades, for instance, one researcher might define “good” grades as a C or better, while another uses a B+ as a starting point for “good.” Another operational definition might describe “tutoring” as “one-on-one assistance by an expert in the field, hired by an educational institution.” Those definitions set limits and establish cut-off points, ensuring consistency and replicability in a study. As the chart shows, an independent variable is the one that causes a dependent variable to change. For example, a researcher might hypothesize that teaching children proper hygiene (the independent variable) will boost their sense of self-esteem (the dependent variable). Or rephrased, a child’s sense of self-esteem depends, in part, on the quality and availability of hygienic resources.

Of course, this hypothesis can also work the other way around. Perhaps a sociologist believes that increasing a child’s sense of self-esteem (the independent variable) will automatically increase or improve habits of hygiene (now the dependent variable). Identifying the independent and dependent variables is very important. As the hygiene example shows, simply identifying two topics, or variables, is not enough: Their prospective relationship must be part of the hypothesis. Just because a sociologist forms an educated prediction of a study’s outcome doesn’t mean data contradicting the hypothesis are not welcome. Sociologists analyze general patterns in response to a study, but they are equally interested in exceptions to patterns.

In a study of education, a researcher might predict that high school dropouts have a hard time finding a rewarding career. While it has become at least a cultural assumption that the higher the education, the higher the salary and degree of career happiness, there are certainly exceptions. People with little education have had stunning careers, and people with advanced degrees have had trouble finding work. A sociologist prepares a hypothesis knowing that results will vary.

While many sociologists rely on the positivist hypothetico-deductive method in their research, others operate from an interpretive approach . While systematic, this approach does not follow the hypothesis-testing model that seeks to make generalizable predictions from quantitative variables. Instead, an interpretive framework seeks to understand social worlds from the point of view of participants, leading to in-depth knowledge. It focuses on qualitative data, or the meanings that guide people’s behaviour. Rather than relying on quantitative instruments like questionnaires or experiments, which can be artificial, the interpretive approach attempts to find ways to get closer to the informants’ lived experience and perceptions. Interpretive research is generally more descriptive or narrative in its findings. It can begin from a deductive approach, by deriving a hypothesis from theory and then seeking to confirm it through methodologies like in-depth interviews.

However, it is ideally suited to an inductive approach in which the hypothesis emerges only after a substantial period of direct observation or interaction with subjects. This type of approach is exploratory in that the researcher also learns as he or she proceeds, sometimes adjusting the research methods or processes midway to respond to new insights and findings as they evolve. Once the preliminary work is done, it’s time for the next research steps: designing and conducting a study, and drawing conclusions. These research methods are discussed below.

Sociologists examine the world, see a problem or interesting pattern, and set out to study it. They use research methods to design a study—perhaps a positivist, quantitative method for conducting research and obtaining data, or perhaps an ethnographic study utilizing an interpretive framework. Planning the research design is a key step in any sociological study. When entering a particular social environment, a researcher must be careful. There are times to remain anonymous and times to be overt. There are times to conduct interviews and times to simply observe. Some participants need to be thoroughly informed; others should not know they are being observed. A researcher would not stroll into a crime-ridden neighbourhood at midnight, calling out, “Any gang members around?” And if a researcher walked into a coffee shop and told the employees they would be observed as part of a study on work efficiency, the self-conscious, intimidated baristas might not behave naturally.

In the 1920s, leaders of a Chicago factory called Hawthorne Works commissioned a study to determine whether or not changing certain aspects of working conditions could increase or decrease worker productivity. Sociologists were surprised when the productivity of a test group increased when the lighting of their workspace was improved. They were even more surprised when productivity improved when the lighting of the workspace was dimmed. In fact almost every change of independent variable—lighting, breaks, work hours—resulted in an improvement of productivity. But when the study was over, productivity dropped again.

Why did this happen? In 1953, Henry A. Landsberger analyzed the study results to answer this question. He realized that employees’ productivity increased because sociologists were paying attention to them. The sociologists’ presence influenced the study results. Worker behaviours were altered not by the lighting but by the study itself. From this, sociologists learned the importance of carefully planning their roles as part of their research design (Franke and Kaul 1978). Landsberger called the workers’ response the Hawthorne effect —people changing their behaviour because they know they are being watched as part of a study.

The Hawthorne effect is unavoidable in some research. In many cases, sociologists have to make the purpose of the study known for ethical reasons. Subjects must be aware that they are being observed, and a certain amount of artificiality may result (Sonnenfeld 1985). Making sociologists’ presence invisible is not always realistic for other reasons. That option is not available to a researcher studying prison behaviours, early education, or the Ku Klux Klan. Researchers cannot just stroll into prisons, kindergarten classrooms, or Ku Klux Klan meetings and unobtrusively observe behaviours. In situations like these, other methods are needed. All studies shape the research design, while research design simultaneously shapes the study. Researchers choose methods that best suit their study topic and that fit with their overall goal for the research.

In planning a study’s design, sociologists generally choose from four widely used methods of social investigation: survey, experiment, field research, and textual or secondary data analysis (or use of existing sources). Every research method comes with plusses and minuses, and the topic of study strongly influences which method or methods are put to use.

As a research method, a survey collects data from subjects who respond to a series of questions about behaviours and opinions, often in the form of a questionnaire. The survey is one of the most widely used positivist research methods. The standard survey format allows individuals a level of anonymity in which they can express personal ideas.

At some point or another, everyone responds to some type of survey. The Statistics Canada census is an excellent example of a large-scale survey intended to gather sociological data. Customers also fill out questionnaires at stores or promotional events, responding to questions such as “How did you hear about the event?” and “Were the staff helpful?” You’ve probably picked up the phone and heard a caller ask you to participate in a political poll or similar type of survey: “Do you eat hot dogs? If yes, how many per month?” Not all surveys would be considered sociological research. Marketing polls help companies refine marketing goals and strategies; they are generally not conducted as part of a scientific study, meaning they are not designed to test a hypothesis or to contribute knowledge to the field of sociology. The results are not published in a refereed scholarly journal, where design, methodology, results, and analyses are vetted.

Often, polls on TV do not reflect a general population, but are merely answers from a specific show’s audience. Polls conducted by programs such as American Idol or Canadian Idol represent the opinions of fans but are not particularly scientific. A good contrast to these are the BBM Ratings, which determine the popularity of radio and television programming in Canada through scientific market research. Sociologists conduct surveys under controlled conditions for specific purposes. Surveys gather different types of information from people. While surveys are not great at capturing the ways people really behave in social situations, they are a great method for discovering how people feel and think—or at least how they say they feel and think. Surveys can track attitudes and opinions, political preferences, reported individual behaviours (such as sleeping, driving, or texting habits), or factual information such as employment status, income, and education levels. A survey targets a specific population , people who are the focus of a study, such as university athletes, international students, or teenagers living with type 1 (juvenile-onset) diabetes.

Most researchers choose to survey a small sector of the population, or a sample : that is, a manageable number of subjects who represent a larger population. The success of a study depends on how well a population is represented by the sample. In a random sample , every person in a population has the same chance of being chosen for the study. According to the laws of probability, random samples represent the population as a whole. For instance, an Ipsos Reid poll, if conducted as a nationwide random sampling, should be able to provide an accurate estimate of public opinion whether it contacts 2,000 or 10,000 people. However the validity of surveys can be threatened when part of the population is inadvertently excluded from the sample (e.g., telephone surveys that rely on land lines exclude people that use only cell phones) or when there is a low response rate. After selecting subjects, the researcher develops a specific plan to ask questions and record responses.

It is important to inform subjects of the nature and purpose of the study upfront. If they agree to participate, researchers thank subjects and offer them a chance to see the results of the study if they are interested. The researcher presents the subjects with an instrument (a means of gathering the information). A common instrument is a structured questionnaire, in which subjects answer a series of set questions. For some topics, the researcher might ask yes-or-no or multiple-choice questions, allowing subjects to choose possible responses to each question.

This kind of quantitative data —research collected in numerical form that can be counted—is easy to tabulate. Just count up the number of “yes” and “no” answers or tabulate the scales of “strongly agree,” “agree,” disagree,” etc. responses and chart them into percentages. This is also their chief drawback however: their artificiality. In real life, there are rarely any unambiguously yes-or-no answers. Questionnaires can also ask more complex questions with more complex answers—beyond “yes,” “no,” “agree,” “strongly agree,” or an option next to a checkbox. In those cases, the answers are subjective, varying from person to person. How do you plan to use your university education? Why do you follow Justin Bieber around the country and attend every concert? Those types of questions require short essay responses, and participants willing to take the time to write those answers will convey personal information about religious beliefs, political views, and morals.

Some topics that reflect internal thought are impossible to observe directly and are difficult to discuss honestly in a public forum. People are more likely to share honest answers if they can respond to questions anonymously. This type of information is qualitative data —results that are subjective and often based on what is seen in a natural setting. Qualitative information is harder to organize and tabulate. The researcher will end up with a wide range of responses, some of which may be surprising. The benefit of written opinions, though, is the wealth of material that they provide.

An interview is a one-on-one conversation between the researcher and the subject, and is a way of conducting surveys on a topic. Interviews are similar to the short answer questions on surveys in that the researcher asks subjects a series of questions. However, participants are free to respond as they wish, without being limited by predetermined choices. In the back-and-forth conversation of an interview, a researcher can ask for clarification, spend more time on a subtopic, or ask additional questions. In an interview, a subject will ideally feel free to open up and answer questions that are often complex. There are no right or wrong answers. The subject might not even know how to answer the questions honestly. Questions such as “How did society’s view of alcohol consumption influence your decision whether or not to take your first sip of alcohol?” or “Did you feel that the divorce of your parents would put a social stigma on your family?” involve so many factors that the answers are difficult to categorize. A researcher needs to avoid steering or prompting the subject to respond in a specific way; otherwise, the results will prove to be unreliable. And, obviously, a sociological interview is not an interrogation. The researcher will benefit from gaining a subject’s trust, from empathizing or commiserating with a subject, and from listening without judgment.

Experiments

You’ve probably tested personal social theories. “If I study at night and review in the morning, I’ll improve my retention skills.” Or, “If I stop drinking soda, I’ll feel better.” Cause and effect. If this, then that. When you test the theory, your results either prove or disprove your hypothesis. One way researchers test social theories is by conducting an experiment , meaning they investigate relationships to test a hypothesis—a scientific approach. There are two main types of experiments: lab-based experiments and natural or field experiments.

In a lab setting, the research can be controlled so that perhaps more data can be recorded in a certain amount of time. In a natural or field-based experiment, the generation of data cannot be controlled but the information might be considered more accurate since it was collected without interference or intervention by the researcher. As a research method, either type of sociological experiment is useful for testing if-then statements: if a particular thing happens, then another particular thing will result.

To set up a lab-based experiment, sociologists create artificial situations that allow them to manipulate variables. Classically, the sociologist selects a set of people with similar characteristics, such as age, class, race, or education. Those people are divided into two groups. One is the experimental group and the other is the control group . The experimental group is exposed to the independent variable(s) and the control group is not. This is similar to pharmaceutical drug trials in which the experimental group is given the test drug and the control group is given a placebo or sugar pill. To test the benefits of tutoring, for example, the sociologist might expose the experimental group of students to tutoring while the control group does not receive tutoring. Then both groups would be tested for differences in performance to see if tutoring had an effect on the experimental group of students. As you can imagine, in a case like this, the researcher would not want to jeopardize the accomplishments of either group of students, so the setting would be somewhat artificial. The test would not be for a grade reflected on their permanent record, for example.

The Stanford Prison Experiment is perhaps one of the most famous sociological experiments ever conducted. In 1971, 24 healthy, middle-class male university students were selected to take part in a simulated jail environment to examine the effects of social setting and social roles on individual psychology and behaviour. They were randomly divided into 12 guards and 12 prisoners. The prisoner subjects were arrested at home and transported blindfolded to the simulated prison in the basement of the psychology building on the campus of Stanford University. Within a day of arriving the prisoners and the guards began to display signs of trauma and sadism respectively. After some prisoners revolted by blockading themselves in their cells, the guards resorted to using increasingly humiliating and degrading tactics to control the prisoners through psychological manipulation. The experiment had to be abandoned after only six days because the abuse had grown out of hand (Haney, Banks, and Zimbardo 1973). While the insights into the social dynamics of authoritarianism it generated were fascinating, the Stanford Prison Experiment also serves as an example of the ethical issues that emerge when experimenting on human subjects.

Making Connections: Sociological Research

An experiment in action: mincome.

A real-life example will help illustrate the experimental process in sociology. Between 1974 and 1979 an experiment was conducted in the small town of Dauphin, Manitoba (the “garden capital of Manitoba”). Each family received a modest monthly guaranteed income—a “mincome”—equivalent to a maximum of 60 percent of the “low-income cut-off figure” (a Statistics Canada measure of poverty, which varies with family size). The income was 50 cents per dollar less for families who had incomes from other sources. Families earning over a certain income level did not receive mincome. Families that were already collecting welfare or unemployment insurance were also excluded. The test families in Dauphin were compared with control groups in other rural Manitoba communities on a range of indicators such as number of hours worked per week, school performance, high school dropout rates, and hospital visits (Forget 2011). A guaranteed annual income was seen at the time as a less costly, less bureaucratic public alternative for addressing poverty than the existing employment insurance and welfare programs. Today it is an active proposal being considered in Switzerland (Lowrey 2013).

Intuitively, it seems logical that lack of income is the cause of poverty and poverty-related issues. One of the main concerns, however, was whether a guaranteed income would create a disincentive to work. The concept appears to challenge the principles of the Protestant work ethic (see the discussion of Max Weber in Chapter 1). The study did find very small decreases in hours worked per week: about 1 percent for men, 3 percent for wives, and 5 percent for unmarried women. Forget (2011) argues this was because the income provided an opportunity for people to spend more time with family and school, especially for young mothers and teenage girls. There were also significant social benefits from the experiment, including better test scores in school, lower high school dropout rates, fewer visits to hospital, fewer accidents and injuries, and fewer mental health issues.

Ironically, due to lack of guaranteed funding (and lack of political interest by the late 1970s), the data and results of the study were not analyzed or published until 2011. The data were archived and sat gathering dust in boxes. The mincome experiment demonstrated the benefits that even a modest guaranteed annual income supplement could have on health and social outcomes in communities. People seem to live healthier lives and get a better education when they do not need to worry about poverty. In her summary of the research, Forget notes that the impact of the income supplement was surprisingly large given that at any one time only about a third of the families were receiving the income and, for some families, the income amount would have been very small. The income benefit was largest for low-income working families but the research showed that the entire community profited. The improvement in overall health outcomes for the community suggest that a guaranteed income would also result in savings for the public health system.

Field Research

The work of sociology rarely happens in limited, confined spaces. Sociologists seldom study subjects in their own offices or laboratories. Rather, sociologists go out into the world. They meet subjects where they live, work, and play. Field research refers to gathering primary data from a natural environment without doing a lab experiment or a survey. It is a research method suited to an interpretive approach rather than to positivist approaches. To conduct field research, the sociologist must be willing to step into new environments and observe, participate, or experience those worlds. In fieldwork, the sociologists, rather than the subjects, are the ones out of their element. The researcher interacts with or observes a person or people, gathering data along the way. The key point in field research is that it takes place in the subject’s natural environment, whether it’s a coffee shop or tribal village, a homeless shelter or a care home, a hospital, airport, mall, or beach resort.

While field research often begins in a specific setting , the study’s purpose is to observe specific behaviours in that setting. Fieldwork is optimal for observing how people behave. It is less useful, however, for developing causal explanations of why they behave that way. From the small size of the groups studied in fieldwork, it is difficult to make predictions or generalizations to a larger population. Similarly, there are difficulties in gaining an objective distance from research subjects. It is difficult to know whether another researcher would see the same things or record the same data. We will look at three types of field research: participant observation, ethnography, and the case study.

Making Connections: Sociology in the Real World

When is sharing not such a good idea.

Choosing a research methodology depends on a number of factors, including the purpose of the research and the audience for whom the research is intended. If we consider the type of research that might go into producing a government policy document on the effectiveness of safe injection sites for reducing the public health risks of intravenous drug use, we would expect public administrators to want “hard” (i.e., quantitative) evidence of high reliability to help them make a policy decision. The most reliable data would come from an experimental or quasi-experimental research model in which a control group can be compared with an experimental group using quantitative measures.

This approach has been used by researchers studying InSite in Vancouver (Marshall et al. 2011; Wood et al. 2006). InSite is a supervised safe-injection site where heroin addicts and other intravenous drug users can go to inject drugs in a safe, clean environment. Clean needles are provided and health care professionals are on hand to intervene in the case of overdose or other medical emergency. It is a controversial program both because heroin use is against the law (the facility operates through a federal ministerial exemption) and because the heroin users are not obliged to quit using or seek therapy. To assess the effectiveness of the program, researchers compared the risky usage of drugs in populations before and after the opening of the facility and geographically near and distant to the facility. The results from the studies have shown that InSite has reduced both deaths from overdose and risky behaviours, such as the sharing of needles, without increasing the levels of crime associated with drug use and addiction.

On the other hand, if the research question is more exploratory (for example, trying to discern the reasons why individuals in the crack smoking subculture engage in the risky activity of sharing pipes), the more nuanced approach of fieldwork is more appropriate. The research would need to focus on the subcultural context, rituals, and meaning of sharing pipes, and why these phenomena override known health concerns. Graduate student Andrew Ivsins at the University of Victoria studied the practice of sharing pipes among 13 habitual users of crack cocaine in Victoria, B.C. (Ivsins 2010). He met crack smokers in their typical setting downtown and used an unstructured interview method to try to draw out the informal norms that lead to sharing pipes. One factor he discovered was the bond that formed between friends or intimate partners when they shared a pipe. He also discovered that there was an elaborate subcultural etiquette of pipe use that revolved around the benefit of getting the crack resin smokers left behind. Both of these motives tended to outweigh the recognized health risks of sharing pipes (such as hepatitis) in the decision making of the users. This type of research was valuable in illuminating the unknown subcultural norms of crack use that could still come into play in a harm reduction strategy such as distributing safe crack kits to addicts.

Participant Observation

In 2000, a comic writer named Rodney Rothman wanted an insider’s view of white-collar work. He slipped into the sterile, high-rise offices of a New York “dot com” agency. Every day for two weeks, he pretended to work there. His main purpose was simply to see if anyone would notice him or challenge his presence. No one did. The receptionist greeted him. The employees smiled and said good morning. Rothman was accepted as part of the team. He even went so far as to claim a desk, inform the receptionist of his whereabouts, and attend a meeting. He published an article about his experience in The New Yorker called “My Fake Job” (2000). Later, he was discredited for allegedly fabricating some details of the story and The New Yorker issued an apology. However, Rothman’s entertaining article still offered fascinating descriptions of the inside workings of a “dot com” company and exemplified the lengths to which a sociologist will go to uncover material.

Rothman had conducted a form of study called participant observation , in which researchers join people and participate in a group’s routine activities for the purpose of observing them within that context. This method lets researchers study a naturally occurring social activity without imposing artificial or intrusive research devices, like fixed questionnaire questions, onto the situation. A researcher might go to great lengths to get a firsthand look into a trend, institution, or behaviour. Researchers temporarily put themselves into “native” roles and record their observations. A researcher might work as a waitress in a diner, or live as a homeless person for several weeks, or ride along with police officers as they patrol their regular beat. Often, these researchers try to blend in seamlessly with the population they study, and they may not disclose their true identity or purpose if they feel it would compromise the results of their research.

At the beginning of a field study, researchers might have a question: “What really goes on in the kitchen of the most popular diner on campus?” or “What is it like to be homeless?” Participant observation is a useful method if the researcher wants to explore a certain environment from the inside. Field researchers simply want to observe and learn. In such a setting, the researcher will be alert and open minded to whatever happens, recording all observations accurately. Soon, as patterns emerge, questions will become more specific, observations will lead to hypotheses, and hypotheses will guide the researcher in shaping data into results. In a study of small-town America conducted by sociological researchers John S. Lynd and Helen Merrell Lynd, the team altered their purpose as they gathered data. They initially planned to focus their study on the role of religion in American towns. As they gathered observations, they realized that the effect of industrialization and urbanization was the more relevant topic of this social group. The Lynds did not change their methods, but they revised their purpose. This shaped the structure of Middletown: A Study in Modern American Culture , their published results (Lynd and Lynd 1959).

The Lynds were upfront about their mission. The townspeople of Muncie, Indiana, knew why the researchers were in their midst. But some sociologists prefer not to alert people to their presence. The main advantage of covert participant observation is that it allows the researcher access to authentic, natural behaviours of a group’s members. The challenge, however, is gaining access to a setting without disrupting the pattern of others’ behaviour. Becoming an inside member of a group, organization, or subculture takes time and effort. Researchers must pretend to be something they are not. The process could involve role playing, making contacts, networking, or applying for a job. Once inside a group, some researchers spend months or even years pretending to be one of the people they are observing. However, as observers, they cannot get too involved. They must keep their purpose in mind and apply the sociological perspective. That way, they illuminate social patterns that are often unrecognized. Because information gathered during participant observation is mostly qualitative, rather than quantitative, the end results are often descriptive or interpretive. The researcher might present findings in an article or book, describing what he or she witnessed and experienced.

This type of research is what journalist Barbara Ehrenreich conducted for her book Nickel and Dimed . One day over lunch with her editor, as the story goes, Ehrenreich mentioned an idea. How can people exist on minimum-wage work? How do low-income workers get by? she wondered. Someone should do a study. To her surprise, her editor responded, Why don’t you do it? That is how Ehrenreich found herself joining the ranks of the low-wage service sector. For several months, she left her comfortable home and lived and worked among people who lacked, for the most part, higher education and marketable job skills. Undercover, she applied for and worked minimum wage jobs as a waitress, a cleaning woman, a nursing home aide, and a retail chain employee. During her participant observation, she used only her income from those jobs to pay for food, clothing, transportation, and shelter. She discovered the obvious: that it’s almost impossible to get by on minimum wage work. She also experienced and observed attitudes many middle- and upper-class people never think about. She witnessed firsthand the treatment of service work employees. She saw the extreme measures people take to make ends meet and to survive. She described fellow employees who held two or three jobs, worked seven days a week, lived in cars, could not pay to treat chronic health conditions, got randomly fired, submitted to drug tests, and moved in and out of homeless shelters. She brought aspects of that life to light, describing difficult working conditions and the poor treatment that low-wage workers suffer.

Ethnography

Ethnography is the extended observation of the social perspective and cultural values of an entire social setting. Researchers seek to immerse themselves in the life of a bounded group, by living and working among them. Often ethnography involves participant observation, but the focus is the systematic observation of an entire community.

The heart of an ethnographic study focuses on how subjects view their own social standing and how they understand themselves in relation to a community. An ethnographic study might observe, for example, a small Newfoundland fishing town, an Inuit community, a village in Thailand, a Buddhist monastery, a private boarding school, or Disney World. These places all have borders. People live, work, study, or vacation within those borders. People are there for a certain reason and therefore behave in certain ways and respect certain cultural norms. An ethnographer would commit to spending a determined amount of time studying every aspect of the chosen place, taking in as much as possible, and keeping careful notes on his or her observations.

A sociologist studying a tribe in the Amazon might learn the language, watch the way villagers go about their daily lives, ask individuals about the meaning of different aspects of activity, study the group’s cosmology and then write a paper about it. To observe a spiritual retreat centre, an ethnographer might sign up for a retreat and attend as a guest for an extended stay, observe and record how people experience spirituality in this setting, and collate the material into results.

The Feminist Perspective: Institutional Ethnography

Dorothy Smith elaborated on traditional ethnography to develop what she calls institutional ethnography (2005). In modern society the practices of everyday life in any particular local setting are often organized at a level that goes beyond what an ethnographer might observe directly. Everyday life is structured by “extralocal,” institutional forms; that is, by the practices of institutions that act upon people from a distance. It might be possible to conduct ethnographic research on the experience of domestic abuse by living in a women’s shelter and directly observing and interviewing victims to see how they form an understanding of their situation. However, to the degree that the women are seeking redress through the criminal justice system a crucial element of the situation would be missing. In order to activate a response from the police or the courts, a set of standard legal procedures must be followed, a “case file” must be opened, legally actionable evidence must be established, forms filled out, etc. All of this allows criminal justice agencies to organize and coordinate the response.

The urgent and immediate experience of the domestic abuse victims needs to be translated into a format that enables distant authorities to take action. Often this is a frustrating and mysterious process in which the immediate needs of individuals are neglected so that needs of institutional processes are met. Therefore to research the situation of domestic abuse victims, an ethnography needs to somehow operate at two levels: the close examination of the local experience of particular women and the simultaneous examination of the extralocal, institutional world through which their world is organized. In order to accomplish this, institutional ethnography focuses on the study of the way everyday life is coordinated through “textually mediated” practices: the use of written documents, standardized bureaucratic categories, and formalized relationships (Smith 1990).

Institutional paperwork translates the specific details of locally lived experience into a standardized format that enables institutions to apply the institution’s understandings, regulations, and operations in different local contexts. The study of these textual practices reveal otherwise inaccessible processes that formal organizations depend on: their formality, their organized character, and their ongoing methods of coordination, etc. An institutional ethnography often begins by following the paper trail that emerges when people interact with institutions: how does a person formulate a narrative about what has happened to him or her in a way that the institution will recognize? How is it translated into the abstract categories on a form or screen that enable an institutional response to be initiated? What is preserved in the translation to paperwork and what is lost? Where do the forms go next? What series of “processing interchanges” take place between different departments or agencies through the circulation of paperwork? How is the paperwork modified and made actionable through this process (e.g., an incident report, warrant request, motion for continuance)?

Smith’s insight is that the shift from the locally lived experience of individuals to the extralocal world of institutions is nothing short of a radical metaphysical shift in worldview. In institutional worlds, meanings are detached from directly lived processes and reconstituted in an organizational time, space, and consciousness that is fundamentally different from their original reference point. For example, the crisis that has led to a loss of employment becomes a set of anonymous criteria that determines one’s eligibility for Employment Insurance.

The unique life of a disabled child becomes a checklist that determines the content of an “individual education program” in the school system, which in turn determines whether funding will be provided for special aid assistants or therapeutic programs. Institutions put together a picture of what has occurred that is not at all the same as what was lived. The ubiquitous but obscure mechanism by which this is accomplished is textually mediated communication . The goal of institutional ethnography therefore is to making “documents or texts visible as constituents of social relations” (Smith 1990). Institutional ethnography is very useful as a critical research strategy. It is an analysis that gives grassroots organizations, or those excluded from the circles of institutional power, a detailed knowledge of how the administrative apparatuses actually work. This type of research enables more effective actions and strategies for change to be pursued.

The Case Study

Sometimes a researcher wants to study one specific person or event. A case study is an in-depth analysis of a single event, situation, or individual. To conduct a case study, a researcher examines existing sources like documents and archival records, conducts interviews, engages in direct observation, and even participant observation, if possible. Researchers might use this method to study a single case of, for example, a foster child, drug lord, cancer patient, criminal, or rape victim. However, a major criticism of the case study as a method is that a developed study of a single case, while offering depth on a topic, does not provide enough evidence to form a generalized conclusion. In other words, it is difficult to make universal claims based on just one person, since one person does not verify a pattern. This is why most sociologists do not use case studies as a primary research method.

However, case studies are useful when the single case is unique. In these instances, a single case study can add tremendous knowledge to a certain discipline. For example, a feral child, also called “wild child,” is one who grows up isolated from human beings. Feral children grow up without social contact and language, elements crucial to a “civilized” child’s development. These children mimic the behaviours and movements of animals, and often invent their own language. There are only about 100 cases of “feral children” in the world. As you may imagine, a feral child is a subject of great interest to researchers. Feral children provide unique information about child development because they have grown up outside of the parameters of “normal” child development. And since there are very few feral children, the case study is the most appropriate method for researchers to use in studying the subject. At age three, a Ukrainian girl named Oxana Malaya suffered severe parental neglect. She lived in a shed with dogs, eating raw meat and scraps. Five years later, a neighbour called authorities and reported seeing a girl who ran on all fours, barking. Officials brought Oxana into society, where she was cared for and taught some human behaviours, but she never became fully socialized. She has been designated as unable to support herself and now lives in a mental institution (Grice 2006). Case studies like this offer a way for sociologists to collect data that may not be collectable by any other method.

Secondary Data or Textual Analysis

While sociologists often engage in original research studies, they also contribute knowledge to the discipline through secondary data or textual analysis . Secondary data do not result from firsthand research collected from primary sources, but are drawn from the already-completed work of other researchers. Sociologists might study texts written by historians, economists, teachers, or early sociologists. They might search through periodicals, newspapers, or magazines from any period in history. Using available information not only saves time and money, but it can add depth to a study. Sociologists often interpret findings in a new way, a way that was not part of an author’s original purpose or intention. To study how women were encouraged to act and behave in the 1960s, for example, a researcher might watch movies, televisions shows, and situation comedies from that period. Or to research changes in behaviour and attitudes due to the emergence of television in the late 1950s and early 1960s, a sociologist would rely on new interpretations of secondary data. Decades from now, researchers will most likely conduct similar studies on the advent of mobile phones, the Internet, or Facebook.

One methodology that sociologists employ with secondary data is content analysis. Content analysis is a quantitative approach to textual research that selects an item of textual content (i.e., a variable) that can be reliably and consistently observed and coded, and surveys the prevalence of that item in a sample of textual output. For example, Gilens (1996) wanted to find out why survey research shows that the American public substantially exaggerates the percentage of African Americans among the poor. He examined whether media representations influence public perceptions and did a content analysis of photographs of poor people in American news magazines. He coded and then systematically recorded incidences of three variables: (1) Race: white, black, indeterminate; (2) Employed: working, not working; and (3) Age. Gilens discovered that not only were African Americans markedly overrepresented in news magazine photographs of poverty, but that the photos also tended to underrepresent “sympathetic” subgroups of the poor—the elderly and working poor—while overrepresenting less sympathetic groups—unemployed, working age adults. Gilens concluded that by providing a distorted representation of poverty, U.S. news magazines “reinforce negative stereotypes of blacks as mired in poverty and contribute to the belief that poverty is primarily a ‘black problem’” (1996).

Social scientists also learn by analyzing the research of a variety of agencies. Governmental departments and global groups, like Statistics Canada or the World Health Organization, publish studies with findings that are useful to sociologists. A public statistic that measures inequality of incomes might be useful for studying who benefited and who lost as a result of the 2008 recession; a demographic profile of different immigrant groups might be compared with data on unemployment to examine the reasons why immigration settlement programs are more effective for some communities than for others. One of the advantages of secondary data is that it is nonreactive (or unobtrusive) research, meaning that it does not include direct contact with subjects and will not alter or influence people’s behaviours. Unlike studies requiring direct contact with people, using previously published data does not require entering a population and the investment and risks inherent in that research process. Using available data does have its challenges. Public records are not always easy to access. A researcher needs to do some legwork to track them down and gain access to records. In some cases there is no way to verify the accuracy of existing data. It is easy, for example, to count how many drunk drivers are pulled over by the police. But how many are not? While it’s possible to discover the percentage of teenage students who drop out of high school, it might be more challenging to determine the number who return to school or get their GED later.

Another problem arises when data are unavailable in the exact form needed or do not include the precise angle the researcher seeks. For example, the salaries paid to professors at universities is often published. But the separate figures do not necessarily reveal how long it took each professor to reach the salary range, what their educational backgrounds are, or how long they have been teaching. In his research, sociologist Richard Sennett uses secondary data to shed light on current trends. In The Craftsman (2008), he studied the human desire to perform quality work, from carpentry to computer programming. He studied the line between craftsmanship and skilled manual labour. He also studied changes in attitudes toward craftsmanship that occurred not only during and after the Industrial Revolution, but also in ancient times. Obviously, he could not have firsthand knowledge of periods of ancient history; he had to rely on secondary data for part of his study. When conducting secondary data or textual analysis, it is important to consider the date of publication of an existing source and to take into account attitudes and common cultural ideals that may have influenced the research. For example, Robert S. Lynd and Helen Merrell Lynd gathered research for their book Middletown: A Study in Modern American Culture in the 1920s. Attitudes and cultural norms were vastly different then than they are now. Beliefs about gender roles, race, education, and work have changed significantly since then. At the time, the study’s purpose was to reveal the truth about small American communities. Today, it is an illustration of 1920s attitudes and values.

Sociologists conduct studies to shed light on human behaviours. Knowledge is a powerful tool that can be used toward positive change. And while a sociologist’s goal is often simply to uncover knowledge rather than to spur action, many people use sociological studies to help improve people’s lives. In that sense, conducting a sociological study comes with a tremendous amount of responsibility. Like any researchers, sociologists must consider their ethical obligation to avoid harming subjects or groups while conducting their research. The Canadian Sociological Association, or CSA, is the major professional organization of sociologists in Canada. The CSA is a great resource for students of sociology as well.

The CSA maintains a code of ethics —formal guidelines for conducting sociological research—consisting of principles and ethical standards to be used in the discipline. It also describes procedures for filing, investigating, and resolving complaints of unethical conduct. These are in line with the Tri-Council Policy Statement on Ethical Conduct for Research Involving Humans (2010) , which applies to any research with human subjects funded by one of the three federal research agencies – the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC), and the Social Sciences and Humanities Research Council of Canada (SSHRC).

Practising sociologists and sociology students have a lot to consider. Some of the guidelines state that researchers must try to be skillful and fair-minded in their work, especially as it relates to their human subjects. Researchers must obtain participants’ informed consent, and inform subjects of the responsibilities and risks of research before they agree to participate. During a study, sociologists must ensure the safety of participants and immediately stop work if a subject becomes potentially endangered on any level. Researchers are required to protect the privacy of research participants whenever possible. Even if pressured by authorities, such as police or courts, researchers are not ethically allowed to release confidential information. Researchers must make results available to other sociologists, must make public all sources of financial support, and must not accept funding from any organization that might cause a conflict of interest or seek to influence the research results for its own purposes. The CSA’s ethical considerations shape not only the study but also the publication of results.

Pioneer German sociologist Max Weber (1864–1920) identified another crucial ethical concern. Weber understood that personal values could distort the framework for disclosing study results. While he accepted that some aspects of research design might be influenced by personal values, he declared it was entirely inappropriate to allow personal values to shape the interpretation of the responses. Sociologists, he stated, must establish value neutrality , a practice of remaining impartial, without bias or judgment, during the course of a study and in publishing results (1949). Sociologists are obligated to disclose research findings without omitting or distorting significant data. Value neutrality does not mean having no opinions. It means striving to overcome personal biases, particularly subconscious biases, when analyzing data. It means avoiding skewing data in order to match a predetermined outcome that aligns with a particular agenda, such as a political or moral point of view. Investigators are ethically obligated to report results, even when they contradict personal views, predicted outcomes, or widely accepted beliefs. Is value neutrality possible?

Many sociologists believe it is impossible to set aside personal values and retain complete objectivity. Individuals inevitably see the world from a partial perspective. Their interests are central to the types of topics they choose, the types of questions they ask, the way they frame their research and the research methodologies they select to pursue it. Moreover, facts, however objective, do not exist in a void. As we noted in Chapter 1, Jürgen Habermas (1972) argues that sociological research has built-in interests quite apart from the personal biases of individual researchers. Positivist sociology has an interest in pursuing types of knowledge that are useful for controlling and administering social life. Interpretive sociology has an interest in pursuing types of knowledge that promote greater mutual understanding and the possibility of consensus among members of society. Critical sociology has an interest in types of knowledge that enable emancipation from power relations and forms of domination in society. In Habermas’ view, sociological knowledge is not disinterested knowledge. This does not discredit the results of sociological research but allows readers to take into account the perspective of the research when judging the validity and applicability of its outcomes.

case study in-depth analysis of a single event, situation, or individual

code of ethics a set of guidelines that the Canadian Sociological Association has established to foster ethical research and professionally responsible scholarship in sociology

content analysis a quantitative approach to textual research that selects an item of textual content that can be reliably and consistently observed and coded, and surveys the prevalence of that item in a sample of textual output

control group an experimental group that is not exposed to the independent variable

correlation when a change in one variable coincides with a change in another variable, but does not necessarily indicate causation

d ependent variable variable changed by another variable

empirical evidence evidence corroborated by direct experience and/or observation

ethnography observing a complete social setting and all that it entails

experiment the testing of a hypothesis under controlled conditions

field research gathering data from a natural environment without doing a lab experiment or a survey

Hawthorne effect when study subjects behave in a certain manner due to their awareness of being observed by a researcher

hypothesis an educated guess with predicted outcomes about the relationship between two or more variables hypothetico-deductive methodologies methodologies based on deducing a prediction from a hypothesis and testing the validity of the hypothesis by whether it correctly predicts observations

independent variable variable that causes change in a dependent variable

inductive approach methodologies that derive a general statement from a series of empirical observations

institutional ethnography the study of the way everyday life is coordinated through institutional, textually mediated practices

interpretive approach a sociological research approach that seeks in-depth understanding of a topic or subject through observation or interaction

interview a one-on-one conversation between a researcher and a subject

literature review a scholarly research step that entails identifying and studying all existing studies on a topic to create a basis for new research

nonreactive unobtrusive research that does not include direct contact with subjects and will not alter or influence people’s behaviours

operational definitions specific explanations of abstract concepts that a researcher plans to study

participant observation immersion by a researcher in a group or social setting in order to make observations from an “insider” perspective

population a defined group serving as the subject of a study

positivist approach a research approach based on the natural science model of knowledge utilizing a hypothetico-deductive formulation of the research question and quantitative data

primary data data collected directly from firsthand experience

qualitative data information based on interpretations of meaning

quantitative data information from research collected in numerical form that can be counted

random sample a study’s participants being randomly selected to serve as a representation of a larger population reliability a measure of a study’s consistency that considers how likely results are to be replicated if a study is reproduced research design a detailed, systematic method for conducting research and obtaining data

sample small, manageable number of subjects that represent the population

scientific method a systematic research method that involves asking a question, researching existing sources, forming a hypothesis, designing and conducting a study, and drawing conclusions

secondary data analysis using data collected by others but applying new interpretations

surveys data collections from subjects who respond to a series of questions about behaviours and opinions, often in the form of a questionnaire

textually mediated communication institutional forms of communication that rely on written documents, texts, and paperwork

validity the degree to which a sociological measure accurately reflects the topic of study

value neutrality a practice of remaining impartial, without bias or judgment during the course of a study and in publishing results

variable a characteristic or measure of a social phenomenon that can take different values

Section Summary

2.1. Approaches to Sociological Research Using the scientific method, a researcher conducts a study in five phases: asking a question, researching existing sources, formulating a hypothesis, conducting a study, and drawing conclusions. The scientific method is useful in that it provides a clear method of organizing a study. Some sociologists conduct scientific research through a positivist framework utilizing a hypothetico-deductive formulation of the research question. Other sociologists conduct scientific research by employing an interpretive framework that is often inductive in nature. Scientific sociological studies often observe relationships between variables. Researchers study how one variable changes another. Prior to conducting a study, researchers are careful to apply operational definitions to their terms and to establish dependent and independent variables.

2.2. Research Methods Sociological research is a fairly complex process. As you can see, a lot goes into even a simple research design. There are many steps and much to consider when collecting data on human behaviour, as well as in interpreting and analyzing data in order to form conclusive results. Sociologists use scientific methods for good reason. The scientific method provides a system of organization that helps researchers plan and conduct the study while ensuring that data and results are reliable, valid, and objective. The many methods available to researchers—including experiments, surveys, field studies, and secondary data analysis—all come with advantages and disadvantages. The strength of a study can depend on the choice and implementation of the appropriate method of gathering research. Depending on the topic, a study might use a single method or a combination of methods. It is important to plan a research design before undertaking a study. The information gathered may in itself be surprising, and the study design should provide a solid framework in which to analyze predicted and unpredicted data.

Table 2.2. Main Sociological Research Methods. Sociological research methods have advantages and disadvantages.

2.3. Ethical Concerns Sociologists and sociology students must take ethical responsibility for any study they conduct. They must first and foremost guarantee the safety of their participants. Whenever possible, they must ensure that participants have been fully informed before consenting to be part of a study. The CSA (Canadian Sociological Association) maintains ethical guidelines that sociologists must take into account as they conduct research. The guidelines address conducting studies, properly using existing sources, accepting funding, and publishing results. Sociologists must try to maintain value neutrality. They must gather and analyze data objectively, setting aside their personal preferences, beliefs, and opinions. They must report findings accurately, even if they contradict personal convictions.

Section Quiz

2.1. Approaches to Sociological Research 1. A measurement is considered ______ if it actually measures what it is intended to measure, according to the topic of the study.

sociological
quantitative

2. Sociological studies test relationships in which change in one ______ causes change in another.

test subject
operational definition

3. In a study, a group of 10-year-old boys are fed doughnuts every morning for a week and then weighed to see how much weight they gained. Which factor is the dependent variable?

the doughnuts
the duration of a week
the weight gained

4. Which statement provides the best operational definition of “childhood obesity”?

children who eat unhealthy foods and spend too much time watching television and playing video games
a distressing trend that can lead to health issues including type 2 diabetes and heart disease
body weight at least 20 percent higher than a healthy weight for a child of that height
the tendency of children today to weigh more than children of earlier generations

2.2. Research Methods 5. Which materials are considered secondary data?

photos and letters given to you by another person
books and articles written by other authors about their studies
information that you have gathered and now have included in your results
responses from participants whom you both surveyed and interviewed

6. What method did Andrew Ivsins use to study crack users in Victoria?

field research
content analysis

7. Why is choosing a random sample an effective way to select participants?

Participants do not know they are part of a study
The researcher has no control over who is in the study
It is larger than an ordinary sample
Everyone has the same chance of being part of the study

8. What research method did John S. Lynd and Helen Merrell Lynd mainly use in their Middletown study?

secondary data
participant observation

9. Which research approach is best suited to the positivist approach?

questionnaire
ethnography
secondary data analysis

10. The main difference between ethnography and other types of participant observation is:

ethnography isn’t based on hypothesis testing
ethnography subjects are unaware they’re being studied
ethnographic studies always involve minority ethnic groups
there is no difference

11. Which best describes the results of a case study?

it produces more reliable results than other methods because of its depth
its results are not generally applicable
it relies solely on secondary data analysis
all of the above

12. Using secondary data is considered an unobtrusive or ________ research method.

nonreactive
nonparticipatory
nonrestrictive
nonconfrontive

2.3. Ethical Concerns 13. Which statement illustrates value neutrality?

Obesity in children is obviously a result of parental neglect and, therefore, schools should take a greater role to prevent it.
In 2003, states like Arkansas adopted laws requiring elementary schools to remove soft drink vending machines from schools.
Merely restricting children’s access to junk food at school is not enough to prevent obesity.
Physical activity and healthy eating are a fundamental part of a child’s education.

14. Which person or organization defined the concept of value neutrality?

Institutional Review Board (IRB)
Peter Rossi
Canadian Sociological Association (CSA)

15. To study the effects of fast food on lifestyle, health, and culture, from which group would a researcher ethically be unable to accept funding?

a fast-food restaurant
a nonprofit health organization
a private hospital
a governmental agency like Health and Social Services

Short Answer

Write down the first three steps of the scientific method. Think of a broad topic that you are interested in and which would make a good sociological study—for example, ethnic diversity in a college, homecoming rituals, athletic scholarships, or teen driving. Now, take that topic through the first steps of the process. For each step, write a few sentences or a paragraph: 1) Ask a question about the topic. 2) Do some research and write down the titles of some articles or books you’d want to read about the topic. 3) Formulate a hypothesis.

2.2.Research Methods

What type of data do surveys gather? For what topics would surveys be the best research method? What drawbacks might you expect to encounter when using a survey? To explore further, ask a research question and write a hypothesis. Then create a survey of about six questions relevant to the topic. Provide a rationale for each question. Now define your population and create a plan for recruiting a random sample and administering the survey.
Imagine you are about to do field research in a specific place for a set time. Instead of thinking about the topic of study itself, consider how you, as the researcher, will have to prepare for the study. What personal, social, and physical sacrifices will you have to make? How will you manage your personal effects? What organizational equipment and systems will you need to collect the data?
Create a brief research design about a topic in which you are passionately interested. Now write a letter to a philanthropic or grant organization requesting funding for your study. How can you describe the project in a convincing yet realistic and objective way? Explain how the results of your study will be a relevant contribution to the body of sociological work already in existence.
Why do you think the CSA crafted such a detailed set of ethical principles? What type of study could put human participants at risk? Think of some examples of studies that might be harmful. Do you think that, in the name of sociology, some researchers might be tempted to cross boundaries that threaten human rights? Why?
Would you willingly participate in a sociological study that could potentially put your health and safety at risk, but had the potential to help thousands or even hundreds of thousands of people? For example, would you participate in a study of a new drug that could cure diabetes or cancer, even if it meant great inconvenience and physical discomfort for you or possible permanent damage?

Further Research

2.1. Approaches to Sociological Research For a historical perspective on the scientific method in sociology, read “The Elements of Scientific Method in Sociology” by F. Stuart Chapin (1914) in the American Journal of Sociology : http://openstaxcollege.org/l/Method-in-Sociology

2.2. Research Methods For information on current real-world sociology experiments, visit: http://openstaxcollege.org/l/Sociology-Experiments

2.3. Ethical Concerns Founded in 1966, the CSA is a nonprofit organization located in Montreal, Quebec, with a membership of 900 researchers, faculty members, students, and practitioners of sociology. Its mission is to promote “research, publication and teaching in Sociology in Canada.” Learn more about this organization at http://www.csa-scs.ca/ .

2.1. Approaches to Sociological Research Merton, Robert. 1968 [1949]. Social Theory and Social Structure . New York: Free Press.

2.2. Research Methods Forget, Evelyn. 2011. “The Town with no Poverty: Using Health Administration Data to Revisit Outcomes of a Canadian Guaranteed Annual Income Field Experiement.” Canadian Public Policy . 37(3): 282-305.

Franke, Richard and James Kaul. 1978. “The Hawthorne Experiments: First Statistical Interpretation.” American Sociological Review 43(5):632–643.

Gilens, Martin. 1996. “Race and Poverty in America: Public Misperceptions and the American News Media.” The Public Opinion Quarterly 60(4):515–541. Grice, Elizabeth. 2006. “Cry of an Enfant Sauvage.” The Telegraph . Retrieved July 20, 2011 ( http://www.telegraph.co.uk/culture/tvandradio/3653890/Cry-of-an-enfant-sauvage.html ).

Haney, C., Banks, W. C., and Zimbardo, P. G. 1973. “Interpersonal Dynamics in a Simulated Prison.” International Journal of Criminology and Penology 1:69–97.

Ivsins, A.K. 2010. “’Got a pipe?’ The social dimensions and functions of crack pipe sharing among crack users in Victoria, BC.” MA thesis, Department of Sociology, University of Victoria. Retrieved February 14, 2014 ( http://dspace.library.uvic.ca:8080/bitstream/handle/1828/3044/Full%20thesis%20Ivsins_CPS.2010_FINAL.pdf?sequence=1 )

Lowrey, Annie. 2013. “Switzerland’s Proposal to Pay People for Being Alive.” The New York Times Magazine. Retrieved February 17, 2014 ( http://www.nytimes.com/2013/11/17/magazine/switzerlands-proposal-to-pay-people-for-being-alive.html?pagewanted=1&_r=2 ).

Lynd, Robert S. and Helen Merrell Lynd. 1959. Middletown: A Study in Modern American Culture . San Diego, CA: Harcourt Brace Javanovich.

Lynd, Staughton. 2005. “Making Middleton.” Indiana Magazine of History 101(3):226–238.

Marshall, B.D.L., M.J. Milloy, E. Wood, J.S.G. Montaner, and T. Kerr. 2011. “Reduction in overdose mortality after the opening of North America’s first medically supervised safer injecting facility: A retrospective population-based study.” Lancet 377(9775):1429–1437.

Rothman, Rodney. 2000. “My Fake Job.” The New Yorker , November 27, 120.

Sennett, Richard. 2008. The Craftsman . New Haven, CT: Yale University Press. Retrieved July 18, 2011 ( http://www.richardsennett.com/site/SENN/Templates/General.aspx?pageid=40 ).

Smith, Dorothy. 1990. “Textually Mediated Social Organization” Pp. 209–234 in Texts, Facts and Femininity: Exploring the Relations of Ruling. London: Routledge.

Smith, Dorothy. 2005. Institutional Ethnography: A Sociology for People. Toronto: Altamira Press.

Sonnenfeld, Jeffery A. 1985. “Shedding Light on the Hawthorne Studies.” Journal of Occupational Behavior 6:125.

Wood, E., M.W. Tyndall, J.S. Montaner, and T. Kerr. 2006. “Summary of findings from the evaluation of a pilot medically supervised safer injecting facility.” Canadian Medical Association Journal 175(11):1399–1404.

2.3. Ethical Concerns Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada, and Social Sciences and Humanities Research Council of Canada. 2010. Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans . Retrieved February 15, 2014 ( http://www.pre.ethics.gc.ca/pdf/eng/tcps2/TCPS_2_FINAL_Web.pdf ).

Canadian Sociological Association. 2012. Statement of Professional Ethics . Retrieved February 15, 2014 ( http://www.csa-scs.ca/files/www/csa/documents/codeofethics/2012Ethics.pdf ).

Habermas, Jürgen. 1972. Knowledge and Human Interests. Boston: Beacon Press

Weber, Max. 1949. Methodology of the Social Sciences . Translated by H. Shils and E. Finch. Glencoe, IL: Free Press.

Solutions to Section Quiz

1. C | 2. C | 3. D | 4. C | 5. B | 6. C | 7. D | 8. C | 9. A | 10. A | 11. B | 12. A | 13. B | 14. D | 15. A

Image Attributions

Figure 2.3. Didn’t they abolish the mandatory census? Then what’s this? by Khosrow Ebrahimpour ( https://www.flickr.com/photos/xosrow/5685345306/in/photolist-9EoT5W-ow4tdu-oeGG4m-oeMEcK-oy2jM2-ovJC8w-oePSRQ-9J2V24-of1Hnu-of243u-of2K2B-of2FHn-owiBSA-owtQN3-of1Ktd-oitLSC-oeVJte-oep8KX-ovEz8w-oeohhF-oew5Xb-oewdWN-owavju-oeMEnV-oweLcN-ovEPGG-ovAQUX-oeo2eL-oeo3Fd-oeoqxh-oxCKnv-ovEzA5-oewFHa-ovHRSz-ow8QtY-oeQY6Y-oeZReR-oeQmHw-oeKXid-oeQLKa-oy6fNT-ow4sVT-oeQMQq-oeQPPr-oeQYbL-ow8hS1-ow4n8v-owiPKS-oeQF41-oeiH5z ) used under CC BY 2.0 ( https://creativecommons.org/licenses/by/2.0/ )

Figure 2.4. Dauphin Canadian Northern Railway Station by Bobak Ha’Eri ( http://commons.wikimedia.org/wiki/File:2009-0520-TrainStation-Dauphin.jpg ) used under CC BY 3.0 license ( http://creativecommons.org/licenses/by/3.0/deed.en )

Figure 2.5. Punk Band by Patrick ( https://www.flickr.com/photos/lordkhan/181561343/in/photostream/ ) used under CC BY 2.0 ( https://creativecommons.org/licenses/by/2.0/ )

Figure 2.6. Crack Cocaine Smokers in Vancouver Alleyway ( http://commons.wikimedia.org/wiki/File:Crack_Cocaine_Smokers_in_Vancouver_Alleyway.jpg ) is in the public domain ( http://en.wikipedia.org/wiki/Public_domain )

Figure 2.8. Muncie, Indiana High School: 1917 by Don O’Brien ( https://www.flickr.com/photos/dok1/3694125269/ ) used under CC BY 2.0 license ( https://creativecommons.org/licenses/by/2.0/ )

Introduction to Sociology - 1st Canadian Edition Copyright © 2014 by William Little and Ron McGivern is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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The Writing Center • University of North Carolina at Chapel Hill

What this handout is about

This handout introduces you to the wonderful world of writing sociology. Before you can write a clear and coherent sociology paper, you need a firm understanding of the assumptions and expectations of the discipline. You need to know your audience, the way they view the world and how they order and evaluate information. So, without further ado, let’s figure out just what sociology is, and how one goes about writing it.

What is sociology, and what do sociologists write about?

Unlike many of the other subjects here at UNC, such as history or English, sociology is a new subject for many students. Therefore, it may be helpful to give a quick introduction to what sociologists do. Sociologists are interested in all sorts of topics. For example, some sociologists focus on the family, addressing issues such as marriage, divorce, child-rearing, and domestic abuse, the ways these things are defined in different cultures and times, and their effect on both individuals and institutions. Others examine larger social organizations such as businesses and governments, looking at their structure and hierarchies. Still others focus on social movements and political protest, such as the American civil rights movement. Finally, sociologists may look at divisions and inequality within society, examining phenomena such as race, gender, and class, and their effect on people’s choices and opportunities. As you can see, sociologists study just about everything. Thus, it is not the subject matter that makes a paper sociological, but rather the perspective used in writing it.

So, just what is a sociological perspective? At its most basic, sociology is an attempt to understand and explain the way that individuals and groups interact within a society. How exactly does one approach this goal? C. Wright Mills, in his book The Sociological Imagination (1959), writes that “neither the life of an individual nor the history of a society can be understood without understanding both.” Why? Well, as Karl Marx observes at the beginning of The Eighteenth Brumaire of Louis Bonaparte (1852), humans “make their own history, but they do not make it just as they please; they do not make it under circumstances chosen by themselves, but under circumstances directly encountered, given and transmitted from the past.” Thus, a good sociological argument needs to balance both individual agency and structural constraints. That is certainly a tall order, but it is the basis of all effective sociological writing. Keep it in mind as you think about your own writing.

Key assumptions and characteristics of sociological writing

What are the most important things to keep in mind as you write in sociology? Pay special attention to the following issues.

The first thing to remember in writing a sociological argument is to be as clear as possible in stating your thesis. Of course, that is true in all papers, but there are a couple of pitfalls common to sociology that you should be aware of and avoid at all cost. As previously defined, sociology is the study of the interaction between individuals and larger social forces. Different traditions within sociology tend to favor one side of the equation over the other, with some focusing on the agency of individual actors and others on structural factors. The danger is that you may go too far in either of these directions and thus lose the complexity of sociological thinking. Although this mistake can manifest itself in any number of ways, three types of flawed arguments are particularly common:

The “ individual argument ” generally takes this form: “The individual is free to make choices, and any outcomes can be explained exclusively through the study of their ideas and decisions.” While it is of course true that we all make our own choices, we must also keep in mind that, to paraphrase Marx, we make these choices under circumstances given to us by the structures of society. Therefore, it is important to investigate what conditions made these choices possible in the first place, as well as what allows some individuals to successfully act on their choices while others cannot.
The “ human nature argument ” seeks to explain social behavior through a quasi-biological argument about humans, and often takes a form such as: “Humans are by nature X, therefore it is not surprising that Y.” While sociologists disagree over whether a universal human nature even exists, they all agree that it is not an acceptable basis of explanation. Instead, sociology demands that you question why we call some behavior natural, and to look into the social factors which have constructed this “natural” state.
The “ society argument ” often arises in response to critiques of the above styles of argumentation, and tends to appear in a form such as: “Society made me do it.” Students often think that this is a good sociological argument, since it uses society as the basis for explanation. However, the problem is that the use of the broad concept “society” masks the real workings of the situation, making it next to impossible to build a strong case. This is an example of reification, which is when we turn processes into things. Society is really a process, made up of ongoing interactions at multiple levels of size and complexity, and to turn it into a monolithic thing is to lose all that complexity. People make decisions and choices. Some groups and individuals benefit, while others do not. Identifying these intermediate levels is the basis of sociological analysis.

Although each of these three arguments seems quite different, they all share one common feature: they assume exactly what they need to be explaining. They are excellent starting points, but lousy conclusions.

Once you have developed a working argument, you will next need to find evidence to support your claim. What counts as evidence in a sociology paper? First and foremost, sociology is an empirical discipline. Empiricism in sociology means basing your conclusions on evidence that is documented and collected with as much rigor as possible. This evidence usually draws upon observed patterns and information from collected cases and experiences, not just from isolated, anecdotal reports. Just because your second cousin was able to climb the ladder from poverty to the executive boardroom does not prove that the American class system is open. You will need more systematic evidence to make your claim convincing. Above all else, remember that your opinion alone is not sufficient support for a sociological argument. Even if you are making a theoretical argument, you must be able to point to documented instances of social phenomena that fit your argument. Logic is necessary for making the argument, but is not sufficient support by itself.

Sociological evidence falls into two main groups:

Quantitative data are based on surveys, censuses, and statistics. These provide large numbers of data points, which is particularly useful for studying large-scale social processes, such as income inequality, population changes, changes in social attitudes, etc.
Qualitative data, on the other hand, comes from participant observation, in-depth interviews, data and texts, as well as from the researcher’s own impressions and reactions. Qualitative research gives insight into the way people actively construct and find meaning in their world.

Quantitative data produces a measurement of subjects’ characteristics and behavior, while qualitative research generates information on their meanings and practices. Thus, the methods you choose will reflect the type of evidence most appropriate to the questions you ask. If you wanted to look at the importance of race in an organization, a quantitative study might use information on the percentage of different races in the organization, what positions they hold, as well as survey results on people’s attitudes on race. This would measure the distribution of race and racial beliefs in the organization. A qualitative study would go about this differently, perhaps hanging around the office studying people’s interactions, or doing in-depth interviews with some of the subjects. The qualitative researcher would see how people act out their beliefs, and how these beliefs interact with the beliefs of others as well as the constraints of the organization.

Some sociologists favor qualitative over quantitative data, or vice versa, and it is perfectly reasonable to rely on only one method in your own work. However, since each method has its own strengths and weaknesses, combining methods can be a particularly effective way to bolster your argument. But these distinctions are not just important if you have to collect your own data for your paper. You also need to be aware of them even when you are relying on secondary sources for your research. In order to critically evaluate the research and data you are reading, you should have a good understanding of the strengths and weaknesses of the different methods.

Units of analysis

Given that social life is so complex, you need to have a point of entry into studying this world. In sociological jargon, you need a unit of analysis. The unit of analysis is exactly that: it is the unit that you have chosen to analyze in your study. Again, this is only a question of emphasis and focus, and not of precedence and importance. You will find a variety of units of analysis in sociological writing, ranging from the individual up to groups or organizations. You should choose yours based on the interests and theoretical assumptions driving your research. The unit of analysis will determine much of what will qualify as relevant evidence in your work. Thus you must not only clearly identify that unit, but also consistently use it throughout your paper.

Let’s look at an example to see just how changing the units of analysis will change the face of research. What if you wanted to study globalization? That’s a big topic, so you will need to focus your attention. Where would you start?

You might focus on individual human actors, studying the way that people are affected by the globalizing world. This approach could possibly include a study of Asian sweatshop workers’ experiences, or perhaps how consumers’ decisions shape the overall system.

Or you might choose to focus on social structures or organizations. This approach might involve looking at the decisions being made at the national or international level, such as the free-trade agreements that change the relationships between governments and corporations. Or you might look into the organizational structures of corporations and measure how they are changing under globalization. Another structural approach would be to focus on the social networks linking subjects together. That could lead you to look at how migrants rely on social contacts to make their way to other countries, as well as to help them find work upon their arrival.

Finally, you might want to focus on cultural objects or social artifacts as your unit of analysis. One fine example would be to look at the production of those tennis shoes the kids seem to like so much. You could look at either the material production of the shoe (tracing it from its sweatshop origins to its arrival on the showroom floor of malls across America) or its cultural production (attempting to understand how advertising and celebrities have turned such shoes into necessities and cultural icons).

Whichever unit of analysis you choose, be careful not to commit the dreaded ecological fallacy. An ecological fallacy is when you assume that something that you learned about the group level of analysis also applies to the individuals that make up that group. So, to continue the globalization example, if you were to compare its effects on the poorest 20% and the richest 20% of countries, you would need to be careful not to apply your results to the poorest and richest individuals.

These are just general examples of how sociological study of a single topic can vary. Because you can approach a subject from several different perspectives, it is important to decide early how you plan to focus your analysis and then stick with that perspective throughout your paper. Avoid mixing units of analysis without strong justification. Different units of analysis generally demand different kinds of evidence for building your argument. You can reconcile the varying levels of analysis, but doing so may require a complex, sophisticated theory, no small feat within the confines of a short paper. Check with your instructor if you are concerned about this happening in your paper.

Typical writing assignments in sociology

So how does all of this apply to an actual writing assignment? Undergraduate writing assignments in sociology may take a number of forms, but they typically involve reviewing sociological literature on a subject; applying or testing a particular concept, theory, or perspective; or producing a small-scale research report, which usually involves a synthesis of both the literature review and application.

The critical review

The review involves investigating the research that has been done on a particular topic and then summarizing and evaluating what you have found. The important task in this kind of assignment is to organize your material clearly and synthesize it for your reader. A good review does not just summarize the literature, but looks for patterns and connections in the literature and discusses the strengths and weaknesses of what others have written on your topic. You want to help your reader see how the information you have gathered fits together, what information can be most trusted (and why), what implications you can derive from it, and what further research may need to be done to fill in gaps. Doing so requires considerable thought and organization on your part, as well as thinking of yourself as an expert on the topic. You need to assume that, even though you are new to the material, you can judge the merits of the arguments you have read and offer an informed opinion of which evidence is strongest and why.

Application or testing of a theory or concept

The application assignment asks you to apply a concept or theoretical perspective to a specific example. In other words, it tests your practical understanding of theories and ideas by asking you to explain how well they apply to actual social phenomena. In order to successfully apply a theory to a new case, you must include the following steps:

First you need to have a very clear understanding of the theory itself: not only what the theorist argues, but also why they argue that point, and how they justify it. That is, you have to understand how the world works according to this theory and how one thing leads to another.
Next you should choose an appropriate case study. This is a crucial step, one that can make or break your paper. If you choose a case that is too similar to the one used in constructing the theory in the first place, then your paper will be uninteresting as an application, since it will not give you the opportunity to show off your theoretical brilliance. On the other hand, do not choose a case that is so far out in left field that the applicability is only superficial and trivial. In some ways theory application is like making an analogy. The last thing you want is a weak analogy, or one that is so obvious that it does not give any added insight. Instead, you will want to choose a happy medium, one that is not obvious but that allows you to give a developed analysis of the case using the theory you chose.
This leads to the last point, which is the analysis. A strong analysis will go beyond the surface and explore the processes at work, both in the theory and in the case you have chosen. Just like making an analogy, you are arguing that these two things (the theory and the example) are similar. Be specific and detailed in telling the reader how they are similar. In the course of looking for similarities, however, you are likely to find points at which the theory does not seem to be a good fit. Do not sweep this discovery under the rug, since the differences can be just as important as the similarities, supplying insight into both the applicability of the theory and the uniqueness of the case you are using.

You may also be asked to test a theory. Whereas the application paper assumes that the theory you are using is true, the testing paper does not makes this assumption, but rather asks you to try out the theory to determine whether it works. Here you need to think about what initial conditions inform the theory and what sort of hypothesis or prediction the theory would make based on those conditions. This is another way of saying that you need to determine which cases the theory could be applied to (see above) and what sort of evidence would be needed to either confirm or disconfirm the theory’s hypothesis. In many ways, this is similar to the application paper, with added emphasis on the veracity of the theory being used.

The research paper

Finally, we reach the mighty research paper. Although the thought of doing a research paper can be intimidating, it is actually little more than the combination of many of the parts of the papers we have already discussed. You will begin with a critical review of the literature and use this review as a basis for forming your research question. The question will often take the form of an application (“These ideas will help us to explain Z.”) or of hypothesis testing (“If these ideas are correct, we should find X when we investigate Y.”). The skills you have already used in writing the other types of papers will help you immensely as you write your research papers.

And so we reach the end of this all-too-brief glimpse into the world of sociological writing. Sociologists can be an idiosyncratic bunch, so paper guidelines and expectations will no doubt vary from class to class, from instructor to instructor. However, these basic guidelines will help you get started.

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Anson, Chris M., and Robert A. Schwegler. 2010. The Longman Handbook for Writers and Readers , 6th ed. New York: Longman.

Cuba, Lee. 2002. A Short Guide to Writing About Social Science , 4th ed. New York: Longman.

Lunsford, Andrea A. 2015. The St. Martin’s Handbook , 8th ed. Boston: Bedford/St Martin’s.

Rosen, Leonard J., and Laurence Behrens. 2003. The Allyn & Bacon Handbook , 5th ed. New York: Longman.

Ruszkiewicz, John J., Christy Friend, Daniel Seward, and Maxine Hairston. 2010. The Scott, Foresman Handbook for Writers , 9th ed. Boston: Pearson Education.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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10 Research questions and testing hypotheses

Soumyajit Patra

This module will teach you about the importance of research questions and hypothesis in social science research. At the end of this module, you will find some digital resources and a bibliography for your further study.

Introduction

Knowledge is contextual and much of it depends on agreement. It is contextual as it has a time-space dimension – knowledge varies from time to time, region to region and from society to society. Take the example of the imperishable plastic bags. These were thought to be very useful even a few years back. But today its harmful effects on environment are known to all and we have started thinking the other way round. The old knowledge has been replaced by the new one.

Knowledge is a matter of agreement as well. A significant portion of what we know is a matter of agreement and belief. Little of it is based on our personal experience and discovery. As we grow up through the process of socialization, we learn to accept (to take it for granted) what everybody around us already knows. If we start questing everything we are taught and try to test instead of accepting what is given, life would be impossible to bear with (Babbie 2004: 5). We have to learn where and how to raise ‘questions’ in our everyday life. This is equally true in case of scientific knowledge. We need to clarify, in this context, the distinction between scientific knowledge and common sense as well as the purpose of scientific research.

2.1 Scientific Knowledge and Common Sense

The distinction between scientific knowledge and common sense would be relevant here. The former is based on logic and is verifiable. The foundation of scientific knowledge is systematic and critical questioning, observation and reasoning. But as Majumdar (2005: 10) defines it, common sense does not ‘take us beyond what are observable. It limits us to events and conclusions that are widely believed as true.’ So, for obvious reasons, knowledge gathered through scientific inquiries may oppose the common sense. Social scientists often emphasize upon the explanatory nature of science that, to a large extent, involves refined and fundamental questioning of the existing knowledge.

2.2 Scientific Research

The purpose of scientific research is to modify or contribute to the existing stock of knowledge through proper inquiry directed by properly framed research questions and reasoning. It is widely believed that there is no ‘absolute’ in science. Scientific knowledge is inclusive and is always open to further investigation and revision. In the words of Das (2004: 21), ‘research may be described as systematic and critical investigation of phenomena towards increasing the stream of knowledge.’ In a similar way Majumdar (2005: 25) writes: ‘The obvious function of research is to add new knowledge to our existing store. Therefore, scientific research is a cumulative process. Since new insights are obtained into the problem investigated, we need to review or modify our earlier beliefs and postulates’.

Learning Outcome

This Module will help you understand different types of research questions and hypotheses that give rise to reliable scientific knowledge. You will also learn how to formulate them.

What are Research Questions?

Researchers have many queries and curiosities in their mind and they try to reach at some satisfactory and valid answers and solutions of these after a careful and meticulous analysis of the relevant data collected through appropriate methods. Research questions are specific questions framed during the initial phase of the research, the answers of which a researcher tries to find out. The research questions set the direction of the entire research process. We can argue following Bryman (2012: 9) that

“A research question is a question that provides an explicit statement of what it is the researcher wants to know about. A research purpose can be presented as a statement … but a question forces the researcher to be more explicit about what is to be investigated”.

4.1 How can Research Questions be framed?

Mere selection of research topic does not direct a researcher to the actual methods to be followed and the specific areas to look at for collecting data. As Patrick White (2009: 33) has argued,

“It is usually much easier to decide upon a topic or area of interest than it is to produce a set of well-structured questions”.

It may be worth noting here that research involves certain definite stages and a researcher starts framing research questions and hypothesis after selection of topic and review of existing literature. The following diagram shows the stages of research before and after the research questions:

Selection of research topic, which is the elementary task of any research, is, however, not an easy task. One has to go through the existing literatures to find out gaps in research. Indian Council of Social Science Research (ICSSR) however publishes trend reports of research done on important themes in sociology and makes us aware of what has so far been done and what needs to be done (Singh 2013). Despite such literature, a researcher has to be very precise in focusing his or her attention while framing research questions. When, after going through the existing literatures on the concerned area, the researcher finally specifies the objectives of the study, he or she is better able to frame his or her research questions. Research questions can also be framed on the basis common sense.

De Vaus (2002) has provided us with some examples that can guide us in developing research questions particularly for descriptive researches. These are:
What is the time frame of our interest?
What is the geographical location of our interest?
Is our interest in broad description or in comparing and specifying patterns for subgroups?
What aspect of the topic are we interested in?
How abstract is our interest?

The research questions of explanatory studies mostly focus on delving the causal relationships between different variables. Naturally the ‘why-questions’ are more important in explanatory researches than the ‘what-questions’, which forms the basis of descriptive studies. According to Babbie (2008: 99), descriptive studies answer questions of what, where, when and how, exploratory studies questions of why? However, the suggestions of Ramkrishna Mukherjee (1993) can be helpful for formulating research questions for any type research in social sciences.

Calling his approach as ‘inductive-inferential method’ Mukherjee ( Ibid .) argues that a social scientist should try to find out the answer of the following questions:

What is it?

What will it be?

What should it be?

For obvious reasons when a researcher deals with the first two questions, i.e. ‘what is it?’ and ‘how is it?’ the orientation of her research is descriptive and classificatory (see also Bose 1997). As soon as she incorporates the question ‘why is it’, her work becomes more explanatory in its spirit. When a social scientist’s research questions include the fourth and fifth questions as well, it becomes a diagnostic study. There can be a reasonable debate among the positivists regarding the inclusion of the fifth question as they believe that the questions like ‘what should it be?’ involve value judgements. However, you canunderstand that a comprehensive research should be based on all the questions mentioned above. In many cases, the researchers deal with a number of research questions, but do not clearly state which questions are more important, or how the questions are related. Such a multiplicity of questions can lead to the problem of lack of focus (Andrews 2003). The researchers should select the number of research questions for her or his study considering the time-cost-labour components of the work. Time, labour and cost of the study would proportionately be increased with the increase in the number of research questions. Too many research questions are difficult to manage as well.

2 Features of Research Questions?

Good research questions that lead to proper research findings have some important features (White 2009; De Vaus 2002; Andrews 2003). The following are the most important among them:

Research questions should be interrogative – Research questions should be interrogative in nature, it should not be declarative. For example it should be like this: ‘What is the relationship between educational level and attitude towards the freedom of media?’ A statement like: ‘There may be some relationship between educational level and attitude towards the freedom of media’ is not a research question.

Research questions should be based on the objectives of the study – Research questions should not divert the attention of the researcher from the basic objectives of the study. It should rather try to delve deep into the problem.

Research questions should be specific – There should not be any ambiguity in the research questions. It should be easily understandable and precise as much as possible.

It should be simple but well-structured – Much of the success of a research depends on the research questions. It should be focused and precisely framed. The ‘fallacy of many questions’ (i.e. aiming at ‘more than one inquiry in a single question’) should be avoided (White 2009). The questions should be structured in such a manner that they help the researcher unveil a specific dimension of the problem.

Self-check Exercise -1:

What do you mean by research?

Research is a scientific process of inquiry by which the existing stock of knowledge is either enriched or modified.

Distinguish between scientific knowledge and common sense.

Scientific knowledge is based on logic and is verifiable. The foundation of scientific knowledge is systematic and critical questioning, observation and reasoning. But common sense is gathered from direct day to day experience. Although common sense is not gathered through scientific inquiry it can be helpful in many research works.

What are research questions?

Research questions are specific questions emerged out of the broad problems of research, the answers of which a researcher tries to find out. The research questions set the direction of the entire research process.

What are the features of good research questions?

Research questions should be interrogative. It should not be a statement. A research question should also be specific, understandable and well-structured. Good research questions are based on the objectives of the study.

Distinguish between descriptive and explanatory research.

Descriptive research tries to describe a phenomenon or a situation or a problem. It generally deals with ‘what’ and ‘how’ questions. Explanatory research, on the other hand, tries to explain the ‘cause-effect’ relationships between different variables. This type of research also involves ‘why’ questions along with the ‘what’ and ‘how’ questions.

Research questions and hypothesis

Both research questions and hypotheses are useful in social science research. According to White (2009), the difference between them is that while research questions are interrogative in its form, hypotheses are declarative statements which are intended to be tested during the course of research. Hypotheses can be restructured in the form of questions. But then one should not call it hypothesis.

5.1 What is hypothesis?

When a researcher conceptualizes her research problems, she thinks about it in general terms. Research questions or hypotheses help look at the specific aspects of the problem. So hypotheses or research questions enable us to carry out meaningful analysis. Hypotheses are specific statements about the problem made at the initial stage of the research, which may be proved right or wrong also include things such as households, cities, organizations, schools, and nations. If an attribute does not vary, it is a constant” (Bryman 2012: 48).

Once a hypothesis assumes a relationship between two or more variables, the validity of such assumption, made on the basis of the personal experiences, knowledge and insights of the researcher, is tested through suitable statistical techniques. Hence, hypothesis is ‘[a]n informed speculation, which is set up to be tested, about the possible relationship between two or more variables’ Bryman (2012: 712). If the primary assumptions are proved correct after the analysis of data, they become part of the theory. So it is said that ‘hypothesis provides the link between the empirical world and the theory’ (Majumdar 2005: 78). Hypothesis formulation and testing are closely associated with the quantitative approach to study social phenomena (Jupp 2006).

5.2 Features of a good hypothesis

‘A hypothesis is a specified testable expectation about empirical reality that follows from a more general proposition’ (Babbie 2004: 44). It is the assumption made about the relationship between different variables on the basis of existing knowledge or common sense. But all declarative statements or assumptions are not hypotheses. Let us discuss some examples:

‘The rate of dropout is higher among the girl students’.
‘The rate of dropout varies with gender with the girl students having a higher dropout rate’.

The first assumption is not an example of a good hypothesis as it does not clearly state the two variables. But, the second one is a better one because it clearly mentions gender and rate of dropout as two variables and a relationship between them is assumed.

The features of good hypotheses are as follows:

Hypothesis generally states (predicts) the relationship between two variables.
It is expressed as a statement and not as a question (Payne and Payne 2005: 112)
Hypothesis should be clearly stated, specific and conceptually clear.
It should be consistent with the known laws of nature (Majumdar 2005)
Hypothesis is testable (after the final analysis it may prove to be correct or incorrect).

5.3 Soures of hypotheses

Hypotheses are not ordinary or casual statements about the empirical reality. They emerge through a systematic and logical process. According to Goode and Hatt (1981), there are four possible sources from which hypotheses can emerge. These are:

Culture can furnish hypotheses – Every human society has some distinctive cultural traits. Many social science researches focus on human behaviour or on meaningful social actions. Folkways, mores, values, customs, belief patterns can help formulate hypotheses in these studies. at the end of the analysis (Henn et al 2006).

Hypotheses are formulated at the third stage of the research process (see Diagram 1). According to Goode and Hatt (1981: 56), ‘[a] hypothesis states what we are looking for.’ They write ‘[i]t is a proposition which can be put to a test to determine its validity.’ Hypotheses are primary assumptions about the interrelations of different variables which set the direction of the entire research process. It may be noted that “a variable is simply an attribute on which cases vary. ‘Cases’ can obviously be people, but they can

Hypotheses can emerge from the science itself – In the backdrop of any research there should be one or more theories. Hypotheses are often deducted from a theory to verify or modify some of its basic conclusions. Goode and Hatt ( ibid .) opine that the socialization process, that a student of a particular discipline undergoes, teaches her/him about the promising areas, paradigms, laws, analytical categories, concepts and methods of that particular discipline. This knowledge can help the student to assume some possible causal relationships between some variables that she or he can put to a test for verification.

Hypotheses can be formulated from analogies – Analogies between human society and nature, between two different types of communities are often a fertile source of hypotheses. For obvious reasons, the researcher should take care in making such analogies. Analogies should not be illogical, it should, on the other hand, be consistent with the known laws of nature.

Hypotheses can come out from idiosyncratic, personal experiences of the researcher – The scientist lives in a particular culture or she can encounter some cultural traits of some other cultures. Her personal experiences can help her formulate effective hypotheses.

5.4 Types of hypothesis

Hypothesis can be classified in many ways. Goode and Hatt (1981) categorize them into three types on the basis of the level of abstraction.

pothesis that state the existence of empirical uniformities – Generally these hypotheses are framed when the researchers want to test the ‘common-sense propositions’. In other words, sometimes the researchers are interested to establish the parallels between what people think about a phenomenon and what actually exists. These often lead to the observations of simple differences. In these hypotheses, sometimes, common sense ideas are put into well-defined concepts and then the hypotheses are statistically verified.
Hypothesis that is concerned with complex ideal types – These hypotheses try to focus on the logically assumed relationships existing among empirical uniformities. In particular, these hypotheses ‘lead to specific coincidences of observations’ ( ibid .: 62). For obvious reasons, these types of hypotheses deal with a higher level of abstraction than the hypotheses that are concerned with the existence of empirical uniformities.
thesis that is concerned with the relation of analytical variables – According to Goode and Hatt ( ibid .) these hypotheses deal with the highest level of abstraction. In this case, the researcher analytically formulates a hypothesis that shows a relationship between changes in one aspect of the phenomenon with the actual or assumed changes in another aspect.

Majumdar (2005) has categorized hypothesis into two types – eliminative (or analytic) induction and enumerative induction. In the former case hypotheses are formulated as ‘universal generalization’ and the presence of any contrary evidence leads to its rejection. In case of enumerative induction, a complete enumeration is required to accept or reject the hypothesis. Look at the following examples:

Hypothesis I: Female students score better in Research Methodology course than the male students.

This is an example of eliminative or analytic induction. If any male student is found, who has scored more than the female students, there would be no reason to accept the hypothesis.

Hypothesis II: Ten Percent female students score better in Research Methodology course than the male students.

This is an example of enumerative induction. To accept or reject the hypothesis a complete enumeration is necessary.

5.5 Hypothesis Testing

A researcher formulates a number of hypotheses (sometimes called experimental hypotheses) and all these hypotheses are tested on the basis of data collected for the study. When a researcher wants to test the hypothesis with the help of some statistical techniques, he or she frames what is called null hypothesis. According to Babbie (2004: 49), in connection with hypothesis testing and tests of statistical significance, the hypothesis that suggests that there is no relationship among the variables under study is null hypothesis . Sometimes null hypothesis states that there is no difference between two variables.

Null Hypothesis (denoted by H 0 ): There is no difference between the percentage of male students and the percentage of female students who have got 60 per cent marks in Research Methodology course.

If the data collected for the study show, for example, that in reality there are differences between the percentage of male students and percentage of female students who have scored 60 per cent in Research Methodology course, there are statistical techniques to determine whether the difference found is statistically significant, or we can ignore the difference attributing it simply to chance factors and accept the null hypothesis (H0). If the difference obtained from the collected data is statistically significant the researcher rejects the null hypothesis and accepts the alternative hypothesis. For obvious reasons there may be more than one alternative hypotheses (denoted by: H1, H2, H3 etc) the researcher has to select any one from among the alternatives if the null hypothesis (H0) is rejected. The following are the examples:

Alternative Hypothesis (H 1 ): There is significant difference between the percentage of male students and the percentage of female students who have got 60 per cent marks in Research Methodology course.

Or, Alternative Hypothesis (H 2 ): The percentage of male students is higher than the percentage of female students who have got 60 per cent marks in Research Methodology course. Or,

Alternative Hypothesis (H 3 ): The percentage of female students is higher than the percentage of male students who have got 60 per cent marks in Research Methodology course.

It is not always easy to accept a hypothesis from among the alternatives. The researchers often has to find out what is called crucial instance to take a final decision regarding the acceptance of a hypothesis from among a number of options (alternative hypotheses). Sometimes they have to go through an experiment to decide what actually would be the alternative hypothesis (in the above example whether H2 is correct or H3 is correct. It should be noted that both H2 and H3 cannot be correct at the same time.) The experiment which finally helps to come to a final decision regarding which one should be accepted reasonably from among the hypotheses is called experimentum crucis (Babbie 2004; Majumdar 2005) . There are a number of statistical techniques like Z-test, t-test, χ2-test etc to test the null hypothesis.

Self-check Exercise – 2:

Distinguish between research question and hypothesis.

Both research questions and hypothesis are framed at the initial stage of the research and both help to look at the research problem in a very specific manner. But while the research question is a specific question the answer of which is sought, hypothesis is a declarative statement framed on the basis of the initial assumptions the validity of which is tested with the help of some statistical techniques. Hypotheses are formulated mainly in case of quantitative research.

State any two features of a good hypothesis.

A good hypothesis is specific and it indicates the relationship between two variables.

What is null hypothesis?

In case of hypothesis testing, the hypothesis that states that there is no difference or relationship between two variables under study is called null hypothesis. It is denoted by Ho. The statistical testing of hypothesis starts with null hypothesis. If the test-result tells the researcher to reject the null hypothesis, the researcher accepts alternative hypothesis.

What are alternative hypotheses?

Alternative hypotheses are formulated against the null hypothesis that states that there is some relationship or difference between the variables. These are denoted by H1, H2 etc.

Type I error and Type II error

Although in case of quantitative research, the researcher specifies the variables and puts the null hypothesis to test using some statistical techniques, there are dangers of reaching at wrong decisions even if the researcher resort to scientific techniques in the testing of hypotheses. He or she can commit two types of errors – Type I error and Type II error. When the researcher accepts a hypothesis when it is actually incorrect it is called Type I error. In case of Type II error the test-result tells the researcher to reject a hypothesis when it is actually correct. Let us look into the following examples:

Suppose you are interested to know whether there is any relationship between the education of the mother and that of their daughters. Sociologists generally use χ2 test to determine such relationships statistically. The null hypothesis of such a test would be like this:

H 0: There is no relationship between mothers’ education and daughters’ education.

The alternative hypothesis would be:

H 1: There is a definite relationship between mothers’ education and daughters’ education.

Suppose the calculated value of χ2 forces the researcher to accept the null hypothesis and come to the conclusion that there is no relationship between the education of the mother and that of their daughters. But in reality these two are highly related. This is the example of Type I error.

Now, suppose you are interested to know about the relationship between distance of home from the nearest high road and the number of children of the married women.

The null hypothesis of such a test would be like this:

H 0: There is no relationship between distance of home from the high road and the number of children.

H 1: There is significant relationship between distance of home from the high road and the number of children.

Suppose the calculated value of χ2 forces the researcher to reject the null hypothesis and come to the conclusion that there is significant relationship between distance of home from the nearest high road and the number of children married women have. It is not difficult to understand that any such relationship between these two is absurd. This is the example of Type II error.

Hypothesis and qualitative research

It has been said that hypothesis is generally associated with quantitative research. But it would be wrong to assume that in qualitative studies, they are irrelevant. According to Jupp (2006), some qualitative researches aim at describing the nature, contexts and consequences of social interactions, social relationships and the process of creations of meanings. These studies also start with some assumptions about the social realities which can be treated as hypotheses. Obviously, these hypotheses do not indicate the relationships between variables. Hypothesis testing in ‘qualitative research is a continuous process, involving the search for cases or contexts that do not square with the assertions being made, rather than a once-and-for-all event’ (Jupp 2006: 138). This is the process of analytical induction and when contrary evidences or what is called crucial instances challenge the conclusions of previous study they are modified or rejected. New hypotheses are then framed in the light of new information or experiences and again their validity is checked.

The topic of any research, which the title of the dissertation signifies, indicates the broad area of research. It is often easy to decide about a topic of research. But, a researcher has to be precise in focusing his or her attention while framing his/her research questions. Research questions and hypotheses are framed to specify the areas in which the researcher concentrates. Research questions are interrogative whereas hypotheses are declarative statements. When the researcher finalizes the specific objectives of the study, he or she is better able to frame his research questions or hypotheses. The researcher tries to find out the answers of the research questions framed at the beginning of the study. Hypotheses or the assumptions.

Andrews, R. Research Questions. London: Continuum, 2003.
Babbie, E. The Practice of Social Research . Australia: Thomson Wadsworth, 2004.
Bose, P. K. “Problems and Paradoxes of Inductive Social Science: A Critique of Ramkrishna Mukherjee”.
Sociological Bulletin 46, no. 2 (1997): 153-171.
Bryman, A, Quantity and Quality in Social Research. London: Routledge, 1988.
…….. Social Research Methods. Oxford: Oxford University Press, 2012. Das, D. K. L. Practice of Social Research. Jaipur: Rawat Publications, 2004.
Goode, W. J. and Hatt, P. K. Methods in Social Research. Auckland: McGraw – Hill International Book Company, 1981.
Henn, M. et. al. A Short Introduction to Social Research, London: Sage Publications, 2006.
Jupp, V. The Sage Dictionary of Social Research Methods. London: Sage Publications, 2006.
Majumdar, P. K. Research Methods in Social Science. New Delhi: Viva Books Pvt. Ltd., 2005.
Mukherjee, R. Systematic Sociology. New Delhi: Sage Publications, 1993.
Payne, G. and Payne, J. Key Concepts in Social Research. London: Sage Publications, 2005.
Singh, Yogendra. ICSSR Research Surveys and Explorations: Indian Sociology. Box Set, Vols 1-3. New Delhi: Oxford, 2013.
Vaus, De D, Surveys in Social Research. London: Routledge, 2002.
White, P. Developing Research Questions: A Guide for Social Scientists. New York: Palgrave Macmillan, 2009.

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How to Form a Hypothesis in Sociology

The Difference Between Physical Science & Social Science

The hypothesis is the basis for scientific inquiry. A hypothesis is like a thesis statement, in that it is a summation of the focus and purpose of your research. Sociology, like other social sciences that study the complex workings of society, produces findings that are open to interpretation, often expressed as statistics. By forming a strong hypothesis, the reader will know what to look for in your collected data.

Look at some aspect of society and find something that interests you. For instance, if you are a smoker or know someone who smokes, look into the impact of smoking on society.

Narrow your focus to something specific. What aspect of society would smoking affect? For example: How many hours in a week are lost to smoking breaks?

Much of sociology deals with statistical analysis, so ask yourself if this is something that can be tested and expressed mathematically. The inclusion of hard data in the form of numbers will give credit and authority to your interpretation and opinion. Your hypothesis, test, and results should be replicable by another researcher.

Make an educated guess about what your results will be. Your hypothesis is an assumption made from your own knowledge or common sense. Be as specific as you can, as it will make your conclusions more definitive. For example: instead of saying "I believe smoking wastes productive time through smoke breaks," make an assumption at how many hours will be lost.

Treat your hypothesis like a question, not a statement. A hypothesis is not a concrete argument; it is an assumption that you are looking to either prove or disprove. Don't be afraid of being disproved by your research.

Create a model for testing your hypothesis. Ask yourself at every step of the model creation, "Will this give me data that relate to my hypothesis?"

What Are the Disadvantages of a Statistical Analysis?

Types of Observation in the Scientific Method

What Makes an Experiment Testable?

Advantages and Disadvantages of Inductive Reasoning

Surveys vs. Experiments

Methods and Types of Qualitative Research

What Is Intraobserver Reliability?

How to Identify a Research Problem

SociologyGuide.com: Hypothesis

Luis Delgado has been writing since 2002. He has written reviews, news stories and short fiction for various websites and publications concerning "geek" culture and interests. He holds a Bachelor of Arts in English from California State University, Stanislaus.

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Home » What is a Hypothesis – Types, Examples and Writing Guide

What is a Hypothesis – Types, Examples and Writing Guide

Table of Contents

Definition:

Hypothesis is an educated guess or proposed explanation for a phenomenon, based on some initial observations or data. It is a tentative statement that can be tested and potentially proven or disproven through further investigation and experimentation.

Hypothesis is often used in scientific research to guide the design of experiments and the collection and analysis of data. It is an essential element of the scientific method, as it allows researchers to make predictions about the outcome of their experiments and to test those predictions to determine their accuracy.

Types of Hypothesis

Types of Hypothesis are as follows:

Research Hypothesis

A research hypothesis is a statement that predicts a relationship between variables. It is usually formulated as a specific statement that can be tested through research, and it is often used in scientific research to guide the design of experiments.

Null Hypothesis

The null hypothesis is a statement that assumes there is no significant difference or relationship between variables. It is often used as a starting point for testing the research hypothesis, and if the results of the study reject the null hypothesis, it suggests that there is a significant difference or relationship between variables.

Alternative Hypothesis

An alternative hypothesis is a statement that assumes there is a significant difference or relationship between variables. It is often used as an alternative to the null hypothesis and is tested against the null hypothesis to determine which statement is more accurate.

Directional Hypothesis

A directional hypothesis is a statement that predicts the direction of the relationship between variables. For example, a researcher might predict that increasing the amount of exercise will result in a decrease in body weight.

Non-directional Hypothesis

A non-directional hypothesis is a statement that predicts the relationship between variables but does not specify the direction. For example, a researcher might predict that there is a relationship between the amount of exercise and body weight, but they do not specify whether increasing or decreasing exercise will affect body weight.

Statistical Hypothesis

A statistical hypothesis is a statement that assumes a particular statistical model or distribution for the data. It is often used in statistical analysis to test the significance of a particular result.

Composite Hypothesis

A composite hypothesis is a statement that assumes more than one condition or outcome. It can be divided into several sub-hypotheses, each of which represents a different possible outcome.

Empirical Hypothesis

An empirical hypothesis is a statement that is based on observed phenomena or data. It is often used in scientific research to develop theories or models that explain the observed phenomena.

Simple Hypothesis

A simple hypothesis is a statement that assumes only one outcome or condition. It is often used in scientific research to test a single variable or factor.

Complex Hypothesis

A complex hypothesis is a statement that assumes multiple outcomes or conditions. It is often used in scientific research to test the effects of multiple variables or factors on a particular outcome.

Applications of Hypothesis

Hypotheses are used in various fields to guide research and make predictions about the outcomes of experiments or observations. Here are some examples of how hypotheses are applied in different fields:

Science : In scientific research, hypotheses are used to test the validity of theories and models that explain natural phenomena. For example, a hypothesis might be formulated to test the effects of a particular variable on a natural system, such as the effects of climate change on an ecosystem.
Medicine : In medical research, hypotheses are used to test the effectiveness of treatments and therapies for specific conditions. For example, a hypothesis might be formulated to test the effects of a new drug on a particular disease.
Psychology : In psychology, hypotheses are used to test theories and models of human behavior and cognition. For example, a hypothesis might be formulated to test the effects of a particular stimulus on the brain or behavior.
Sociology : In sociology, hypotheses are used to test theories and models of social phenomena, such as the effects of social structures or institutions on human behavior. For example, a hypothesis might be formulated to test the effects of income inequality on crime rates.
Business : In business research, hypotheses are used to test the validity of theories and models that explain business phenomena, such as consumer behavior or market trends. For example, a hypothesis might be formulated to test the effects of a new marketing campaign on consumer buying behavior.
Engineering : In engineering, hypotheses are used to test the effectiveness of new technologies or designs. For example, a hypothesis might be formulated to test the efficiency of a new solar panel design.

How to write a Hypothesis

Here are the steps to follow when writing a hypothesis:

Identify the Research Question

The first step is to identify the research question that you want to answer through your study. This question should be clear, specific, and focused. It should be something that can be investigated empirically and that has some relevance or significance in the field.

Conduct a Literature Review

Before writing your hypothesis, it’s essential to conduct a thorough literature review to understand what is already known about the topic. This will help you to identify the research gap and formulate a hypothesis that builds on existing knowledge.

Determine the Variables

The next step is to identify the variables involved in the research question. A variable is any characteristic or factor that can vary or change. There are two types of variables: independent and dependent. The independent variable is the one that is manipulated or changed by the researcher, while the dependent variable is the one that is measured or observed as a result of the independent variable.

Formulate the Hypothesis

Based on the research question and the variables involved, you can now formulate your hypothesis. A hypothesis should be a clear and concise statement that predicts the relationship between the variables. It should be testable through empirical research and based on existing theory or evidence.

Write the Null Hypothesis

The null hypothesis is the opposite of the alternative hypothesis, which is the hypothesis that you are testing. The null hypothesis states that there is no significant difference or relationship between the variables. It is important to write the null hypothesis because it allows you to compare your results with what would be expected by chance.

Refine the Hypothesis

After formulating the hypothesis, it’s important to refine it and make it more precise. This may involve clarifying the variables, specifying the direction of the relationship, or making the hypothesis more testable.

Examples of Hypothesis

Here are a few examples of hypotheses in different fields:

Psychology : “Increased exposure to violent video games leads to increased aggressive behavior in adolescents.”
Biology : “Higher levels of carbon dioxide in the atmosphere will lead to increased plant growth.”
Sociology : “Individuals who grow up in households with higher socioeconomic status will have higher levels of education and income as adults.”
Education : “Implementing a new teaching method will result in higher student achievement scores.”
Marketing : “Customers who receive a personalized email will be more likely to make a purchase than those who receive a generic email.”
Physics : “An increase in temperature will cause an increase in the volume of a gas, assuming all other variables remain constant.”
Medicine : “Consuming a diet high in saturated fats will increase the risk of developing heart disease.”

Purpose of Hypothesis

The purpose of a hypothesis is to provide a testable explanation for an observed phenomenon or a prediction of a future outcome based on existing knowledge or theories. A hypothesis is an essential part of the scientific method and helps to guide the research process by providing a clear focus for investigation. It enables scientists to design experiments or studies to gather evidence and data that can support or refute the proposed explanation or prediction.

The formulation of a hypothesis is based on existing knowledge, observations, and theories, and it should be specific, testable, and falsifiable. A specific hypothesis helps to define the research question, which is important in the research process as it guides the selection of an appropriate research design and methodology. Testability of the hypothesis means that it can be proven or disproven through empirical data collection and analysis. Falsifiability means that the hypothesis should be formulated in such a way that it can be proven wrong if it is incorrect.

In addition to guiding the research process, the testing of hypotheses can lead to new discoveries and advancements in scientific knowledge. When a hypothesis is supported by the data, it can be used to develop new theories or models to explain the observed phenomenon. When a hypothesis is not supported by the data, it can help to refine existing theories or prompt the development of new hypotheses to explain the phenomenon.

When to use Hypothesis

Here are some common situations in which hypotheses are used:

In scientific research , hypotheses are used to guide the design of experiments and to help researchers make predictions about the outcomes of those experiments.
In social science research , hypotheses are used to test theories about human behavior, social relationships, and other phenomena.
I n business , hypotheses can be used to guide decisions about marketing, product development, and other areas. For example, a hypothesis might be that a new product will sell well in a particular market, and this hypothesis can be tested through market research.

Characteristics of Hypothesis

Here are some common characteristics of a hypothesis:

Testable : A hypothesis must be able to be tested through observation or experimentation. This means that it must be possible to collect data that will either support or refute the hypothesis.
Falsifiable : A hypothesis must be able to be proven false if it is not supported by the data. If a hypothesis cannot be falsified, then it is not a scientific hypothesis.
Clear and concise : A hypothesis should be stated in a clear and concise manner so that it can be easily understood and tested.
Based on existing knowledge : A hypothesis should be based on existing knowledge and research in the field. It should not be based on personal beliefs or opinions.
Specific : A hypothesis should be specific in terms of the variables being tested and the predicted outcome. This will help to ensure that the research is focused and well-designed.
Tentative: A hypothesis is a tentative statement or assumption that requires further testing and evidence to be confirmed or refuted. It is not a final conclusion or assertion.
Relevant : A hypothesis should be relevant to the research question or problem being studied. It should address a gap in knowledge or provide a new perspective on the issue.

Advantages of Hypothesis

Hypotheses have several advantages in scientific research and experimentation:

Guides research: A hypothesis provides a clear and specific direction for research. It helps to focus the research question, select appropriate methods and variables, and interpret the results.
Predictive powe r: A hypothesis makes predictions about the outcome of research, which can be tested through experimentation. This allows researchers to evaluate the validity of the hypothesis and make new discoveries.
Facilitates communication: A hypothesis provides a common language and framework for scientists to communicate with one another about their research. This helps to facilitate the exchange of ideas and promotes collaboration.
Efficient use of resources: A hypothesis helps researchers to use their time, resources, and funding efficiently by directing them towards specific research questions and methods that are most likely to yield results.
Provides a basis for further research: A hypothesis that is supported by data provides a basis for further research and exploration. It can lead to new hypotheses, theories, and discoveries.
Increases objectivity: A hypothesis can help to increase objectivity in research by providing a clear and specific framework for testing and interpreting results. This can reduce bias and increase the reliability of research findings.

Limitations of Hypothesis

Some Limitations of the Hypothesis are as follows:

Limited to observable phenomena: Hypotheses are limited to observable phenomena and cannot account for unobservable or intangible factors. This means that some research questions may not be amenable to hypothesis testing.
May be inaccurate or incomplete: Hypotheses are based on existing knowledge and research, which may be incomplete or inaccurate. This can lead to flawed hypotheses and erroneous conclusions.
May be biased: Hypotheses may be biased by the researcher’s own beliefs, values, or assumptions. This can lead to selective interpretation of data and a lack of objectivity in research.
Cannot prove causation: A hypothesis can only show a correlation between variables, but it cannot prove causation. This requires further experimentation and analysis.
Limited to specific contexts: Hypotheses are limited to specific contexts and may not be generalizable to other situations or populations. This means that results may not be applicable in other contexts or may require further testing.
May be affected by chance : Hypotheses may be affected by chance or random variation, which can obscure or distort the true relationship between variables.

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How to Write a Great Hypothesis

Hypothesis Format, Examples, and Tips

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Amy Morin, LCSW, is a psychotherapist and international bestselling author. Her books, including "13 Things Mentally Strong People Don't Do," have been translated into more than 40 languages. Her TEDx talk, "The Secret of Becoming Mentally Strong," is one of the most viewed talks of all time.

Verywell / Alex Dos Diaz

The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis, operational definitions, types of hypotheses, hypotheses examples.

Collecting Data

Frequently Asked Questions

A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study.

One hypothesis example would be a study designed to look at the relationship between sleep deprivation and test performance might have a hypothesis that states: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:

Forming a question
Performing background research
Creating a hypothesis
Designing an experiment
Collecting data
Analyzing the results
Drawing conclusions
Communicating the results

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. It is only at this point that researchers begin to develop a testable hypothesis. Unless you are creating an exploratory study, your hypothesis should always explain what you expect to happen.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore a number of factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment do not support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."

In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk wisdom that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."

Elements of a Good Hypothesis

So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:

Is your hypothesis based on your research on a topic?
Can your hypothesis be tested?
Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the journal articles you read . Many authors will suggest questions that still need to be explored.

To form a hypothesis, you should take these steps:

Collect as many observations about a topic or problem as you can.
Evaluate these observations and look for possible causes of the problem.
Create a list of possible explanations that you might want to explore.
After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

In the scientific method , falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that if something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.

For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions are important because many things can be measured in a number of different ways. One of the basic principles of any type of scientific research is that the results must be replicable. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. How would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.

In order to measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming other people. In this situation, the researcher might utilize a simulated task to measure aggressiveness.

Hypothesis Checklist

Does your hypothesis focus on something that you can actually test?
Does your hypothesis include both an independent and dependent variable?
Can you manipulate the variables?
Can your hypothesis be tested without violating ethical standards?

The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:

Simple hypothesis : This type of hypothesis suggests that there is a relationship between one independent variable and one dependent variable.
Complex hypothesis : This type of hypothesis suggests a relationship between three or more variables, such as two independent variables and a dependent variable.
Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative sample of the population and then generalizes the findings to the larger group.
Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.

A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the dependent variable if you change the independent variable .

The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."

A few examples of simple hypotheses:

"Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
Complex hypothesis: "Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."
"Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."

Examples of a complex hypothesis include:

"People with high-sugar diets and sedentary activity levels are more likely to develop depression."
"Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."

Examples of a null hypothesis include:

"Children who receive a new reading intervention will have scores different than students who do not receive the intervention."
"There will be no difference in scores on a memory recall task between children and adults."

Examples of an alternative hypothesis:

"Children who receive a new reading intervention will perform better than students who did not receive the intervention."
"Adults will perform better on a memory task than children."

Collecting Data on Your Hypothesis

Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.

Descriptive Research Methods

Descriptive research such as case studies , naturalistic observations , and surveys are often used when it would be impossible or difficult to conduct an experiment . These methods are best used to describe different aspects of a behavior or psychological phenomenon.

Once a researcher has collected data using descriptive methods, a correlational study can then be used to look at how the variables are related. This type of research method might be used to investigate a hypothesis that is difficult to test experimentally.

Experimental Research Methods

Experimental methods are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).

Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually cause another to change.

A Word From Verywell

The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.

Some examples of how to write a hypothesis include:

"Staying up late will lead to worse test performance the next day."
"People who consume one apple each day will visit the doctor fewer times each year."
"Breaking study sessions up into three 20-minute sessions will lead to better test results than a single 60-minute study session."

The four parts of a hypothesis are:

The research question
The independent variable (IV)
The dependent variable (DV)
The proposed relationship between the IV and DV

Castillo M. The scientific method: a need for something better? . AJNR Am J Neuroradiol. 2013;34(9):1669-71. doi:10.3174/ajnr.A3401

Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Model Answers

Q: Discuss the importance and sources of hypothesis in social research.

Question asked in UPSC Sociology 2020 Paper 1. Download our app for last 20 year question with model answers.

Model Answer:

Importance of Hypothesis in Social Research

Hypothesis in social research refers to a tentative statement or assumption about the relationship between two or more variables. It is a testable prediction that serves as a starting point for conducting a study. Hypotheses are important in social research for several reasons:

1. Direction and focus: Hypotheses provide a clear direction and focus for the research. They help researchers identify the variables that need to be studied and the relationships that need to be explored. For example, a hypothesis might state that “ higher levels of education lead to higher income levels. ” This statement provides a clear direction for the researcher to investigate the relationship between education and income.

2. Basis for research design: Hypotheses serve as the foundation for designing a research study. They help researchers choose the appropriate methods, techniques, and tools to collect and analyze data. For instance, if a researcher wants to test the hypothesis that “ participation in sports reduces the likelihood of engaging in criminal behavior, ” they might design a study that compares crime rates among individuals who participate in sports and those who do not.

3. Testability: Hypotheses are testable statements that can be either supported or refuted by empirical evidence. This testability is crucial for the scientific process, as it allows researchers to build on existing knowledge and contribute to the understanding of social phenomena. For example, if a hypothesis states that “ social media use increases feelings of loneliness, ” researchers can collect data on social media usage and loneliness levels to test this assumption.

4. Explanation and prediction: Hypotheses help researchers explain and predict social phenomena. By identifying relationships between variables, hypotheses can provide insights into the underlying mechanisms and processes that drive social behavior. For instance, a hypothesis that “ unemployment leads to increased crime rates, ” might suggest that addressing unemployment could help reduce crime.

Sources of hypothesis in social research:

1. Theory: Hypotheses can be derived from existing theories in the field. Theories provide a framework for understanding social phenomena and can suggest relationships between variables that can be tested through research. For example, social learning theory might suggest the hypothesis that “ children who witness violence in their homes are more likely to exhibit aggressive behavior. “

2. Previous research: Hypotheses can be based on the findings of previous studies. Researchers can build on existing knowledge by testing new relationships or exploring the same relationships in different contexts. For example, if a previous study found a relationship between poverty and crime in urban areas, a researcher might hypothesize that the same relationship exists in rural areas.

3. Observations and personal experiences: Researchers can develop hypotheses based on their own observations and experiences. These insights can provide a starting point for investigating social phenomena. For example, a researcher who notices a high rate of teenage pregnancy in their community might hypothesize that a lack of access to sexual education is a contributing factor.

4. Expert opinions and literature reviews: Consulting experts in the field and reviewing existing literature can help researchers identify gaps in knowledge and generate hypotheses. For instance, a review of research on the effects of social media on mental health might reveal conflicting findings, leading a researcher to hypothesize that certain factors, such as the type of social media platform or the amount of time spent online, might moderate these effects.

In conclusion, hypotheses play a crucial role in social research by providing direction, focus, and a basis for research design. They are derived from various sources, including theory, previous research, observations, and expert opinions. By testing hypotheses, researchers can contribute to the understanding of social phenomena and inform policies and interventions aimed at addressing social issues.

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Hypotheses
18. Hypotheses. When researchers do not have predictions about what they will find, they conduct research to answer a question or questions, with an open-minded desire to know about a topic, or to help develop hypotheses for later testing. In other situations, the purpose of research is to test a specific hypothesis or hypotheses.
2.1 Approaches to Sociological Research
A hypothesis is an explanation for a phenomenon based on a conjecture about the relationship between the phenomenon and one or more causal factors. In sociology, the hypothesis will often predict how one form of human behavior influences another. For example, a hypothesis might be in the form of an "if, then statement."
Research Hypothesis: Definition, Types, Examples and Quick Tips
3. Simple hypothesis. A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, "Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking. 4.
Hypothesis: Functions, Problems, Types ...
There are three major difficulties in the formulation of a hypothesis, they are as follows: Absence of a clear theoretical framework. Lack of ability to utilize that theoretical framework logically. Failure to be acquainted with available research techniques so as to phrase the hypothesis properly. Sometimes the deduction of a hypothesis may be ...
How to Write a Strong Hypothesis
5. Phrase your hypothesis in three ways. To identify the variables, you can write a simple prediction in if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable. If a first-year student starts attending more lectures, then their exam scores will improve.
2.1C: Formulating the Hypothesis
A hypothesis is an assumption or suggested explanation about how two or more variables are related. It is a crucial step in the scientific method and, therefore, a vital aspect of all scientific research. There are no definitive guidelines for the production of new hypotheses. The history of science is filled with stories of scientists claiming ...
2.3: Propositions and Hypotheses
Propositions are specified in the theoretical plane, while hypotheses are specified in the empirical plane. Hence, hypotheses are empirically testable using observed data, and may be rejected if not supported by empirical observations. Of course, the goal of hypothesis testing is to infer whether the corresponding proposition is valid.
Chapter 2. Sociological Research
Approaches to Sociological Research. Using the scientific method, a researcher conducts a study in five phases: asking a question, researching existing sources, formulating a hypothesis, conducting a study, and drawing conclusions. The scientific method is useful in that it provides a clear method of organizing a study.
Sociology
What this handout is about. This handout introduces you to the wonderful world of writing sociology. Before you can write a clear and coherent sociology paper, you need a firm understanding of the assumptions and expectations of the discipline. You need to know your audience, the way they view the world and how they order and evaluate information.
The state of the art of hypothesis testing in the social sciences
e. Explicit avoidance of hypotheses. Overall, NHST was explicitly used about 79% of the time, for an average of 3.2 hypotheses per paper, with an average of 88% of a paper's hypotheses being supported. Moreover, 84% of the studies evaluated the size of their estimates in everyday language.
Research questions and testing hypotheses
According to White (2009), the difference between them is that while research questions are interrogative in its form, hypotheses are declarative statements which are intended to be tested during the course of research. Hypotheses can be restructured in the form of questions. But then one should not call it hypothesis.
How to Form a Hypothesis in Sociology
The hypothesis is the basis for scientific inquiry. A hypothesis is like a thesis statement, in that it is a summation of the focus and purpose of your research. Sociology, like other social sciences that study the complex workings of society, produces findings that are open to interpretation, often expressed as statistics.
What is a Hypothesis
Definition: Hypothesis is an educated guess or proposed explanation for a phenomenon, based on some initial observations or data. It is a tentative statement that can be tested and potentially proven or disproven through further investigation and experimentation. Hypothesis is often used in scientific research to guide the design of experiments ...
PDF Writing a Formal Research Paper in the Social Sciences
For a social science research paper, APA format is typically expected. APA format was developed for the social sciences, so it is followed fairly strictly in these types of papers in both formatting the paper and citing sources. When in doubt, follow APA guidelines. Use peer-reviewed sources for research.
(PDF) Sociological Theory and Practice: Introduction
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A research hypothesis is a prediction of the outcome of a study. The prediction may be based on an educated guess or a formal . theory. Example 1 is a hypothesis for a nonexperimental study.
Hypothesis Examples: How to Write a Great Research Hypothesis
What is a hypothesis and how can you write a great one for your research? A hypothesis is a tentative statement about the relationship between two or more variables that can be tested empirically. Find out how to formulate a clear, specific, and testable hypothesis with examples and tips from Verywell Mind, a trusted source of psychology and mental health information.
Term Paper on Hypotheses
Term Paper # 1. Meaning of Hypotheses: Once the problem to be answered in the course of research is finally instituted, the researcher may, if feasible proceed to formulate tentative solutions or answers to it. These proposed solutions or explanations are called hypotheses which the researcher is obliged to test on the basis of fact already ...
Discuss the importance and sources of hypothesis in social research
Hypothesis in social research refers to a tentative statement or assumption about the relationship between two or more variables. It is a testable prediction that serves as a starting point for conducting a study. Hypotheses are important in social research for several reasons: 1. Direction and focus: Hypotheses provide a clear direction and ...
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18 Hypotheses

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2.1 Approaches to Sociological Research

The Scientific Method

Step 1: Ask a Question or Find a Research Topic

Step 2: Review the Literature/Research Existing Sources

Step 3: Formulate a Hypothesis

Step 4: Design and Conduct a Study

Step 5: Draw Conclusions

Step 6: Report Results

Interpretive Framework

Critical Sociology

The Craft of Writing a Strong Hypothesis

Table of Contents

What is a Hypothesis?

Different Types of Hypotheses‌

1. Null hypothesis

2. Alternative hypothesis

3. Simple hypothesis

4. Complex hypothesis

5. Associative and casual hypothesis

6. Empirical hypothesis

7. Statistical hypothesis

Characteristics of a Good Hypothesis

Separating a Hypothesis from a Prediction

Finally, How to Write a Hypothesis

1. Be clear about your research question

2. Carry out a recce

3. Create a 3-dimensional hypothesis

4. Write the first draft

5. Proof your hypothesis

Frequently Asked Questions (FAQs)

2. What is an example of hypothesis?

3. What is an example of null hypothesis?

4. What are the types of research?

5. How to write a hypothesis?

6. What are the 2 types of hypothesis?

7. Difference between research question and research hypothesis?

8. What is plural for hypothesis?

9. What is the red queen hypothesis?

10. Who is known as the father of null hypothesis?

11. When to reject null hypothesis?

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How to Write a Strong Hypothesis | Steps & Examples

Example: Hypothesis

Table of contents

Variables in hypotheses

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Step 1. Ask a question

Step 2. Do some preliminary research

Step 3. Formulate your hypothesis

4. Refine your hypothesis

5. Phrase your hypothesis in three ways

6. Write a null hypothesis

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Shona McCombes

2.3: Propositions and Hypotheses

Chapter 2. Sociological Research

2.2. Research Methods

Introduction to Sociological Research

The Scientific Method

Ask a Question

Research Existing Sources

Formulate a Hypothesis

Experiments

Making Connections: Sociological Research

Field Research