reflection essay about quantitative research

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Qualitative v. Quantitative Research Reflection

Initially, after learning, reading, and researching about these to methods of approaching research in the social work field, I found myself immediately drawn towards quantitative research. Numbers make sense to me and it seems incredibly logical and convenient in theory for me to be able to reduce the human experience into a data set of numbers which I can then calculate and compute to give me a meaningful answer. However, it’s become clear to me over these past few weeks through studying and reading more qualitative studies, that they can be an incredibly valuable resource to actually understanding with and sympathizing with the material we are researching. I believe that qualitative research gives the researcher as well as the person applying the conclusions reached from the research into practice a good understanding of the human component and nuances that go into implementing interventions. Often, it seems that qualitative research can explore the complexities a little more delicately than quantitative research might be able to because the data is becoming synthesized into numbers. Qualitative research does have it’s downfalls though. While all forms of research is subject to various biases, it would seem that qualitative research has a higher risk because, instead of interpreting numbers and calculations, we must interpret human thoughts, feelings, and experiences, which are much less concrete variables. It also may be harder to reach a definitive, mathematically supported answer to the question being posed. Ultimately, I believe mixed methods approach could take the advantages of both methods and combine them so that the research covers both the concrete evidence presented through quantitative researched with the complex insight of the qualitative research.

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A Group Blog on Early American History

On counting: a reflection on quantitative research.

During the heyday of the social history movement in the 1970s and 1980s, tables and numbers abounded in recently-published historical monographs and articles. Historians such as Michael Zuckerman, Philip Greven, and John Demos mined town and probate records to examine the fabric of life in colonial New England towns. Lois Carr, Lorena Walsh and others employed parallel methods in the study of the Chesapeake. For these scholars, systematic quantitative analysis of a vast source base yielded their core arguments. Such methodologies remained influential into the 1990s, when historians like Cornelia Dayton published monographs that presented vast amounts of data even as they broadened their arguments beyond those of previous social histories.

In subsequent decades, the importance of counting and computation seem to have waned. Of course, some areas of early American history—for instance, economic history and the study of the slave trade—remain heavily quantitative, but these sub-fields are exceptions. More frequently, historians who engage in quantitative analysis now do so to offer context or to provide figures that complement other methodologies and support broader arguments.

In other words, whereas older social histories used extensive quantitative data to drive and support their arguments, more recent works, while nonetheless deeply researched, present such data more sparingly. This shift is encapsulated in the reflections of many recent PhDs, whom I’ve often heard make statements along the lines of, “My dissertation had lots of numbers, but I’m moving them to the footnotes or cutting them out for the book.”

What accounts for this shift? One could perhaps point to publishers’ increasing preference for concise monographs, or to the shift from local frameworks to broader continental or Atlantic paradigms. Even more fundamentally, however, I think this shift reflects changes in the kinds of questions early Americanists are choosing to ask and answer, and in the models we select to account for change over time.

To most of The Junto ’s readers, it probably isn’t news that cultural history has gained strength in recent years. As we have become increasingly interested in shifting discourses and practices and in strategic modes of performance and appropriation, it seems that counting has become less essential to the presentation of our research.

I applaud cultural history’s emphasis on eclectic source bases and creative ways of reading them. Indeed, many of the works that I most admire fall into this category, and my own methods certainly align more closely with that of other recent monographs than with that of the older school of social history. But, at the same time, I wonder where the current state of counting leaves historians like me.

Quantitative analysis demands rigor, as does any other mode of inquiry. Yet, more so than other research strategies, counting requires a clear plan at the outset, as it can be difficult to shift one’s approach mid-stream. This summer, I was struck by the number of seemingly small decisions that I was forced to make in the course of my research. I used a combination of Filemaker and Excel to record my findings, and some of my questions concerned how I should construct my databases. Others confronted me at the archives. Which terms and years should I include in my sample of court records? How many court cases do I need to create a sample of sufficient size? How should I deal with incomplete records? How should I record the cases that fall between the categories that I created at the outset of my research?  How I chose to record any one case may have been trivial, but my cumulative choices could have significant consequences for overall findings.

I know that I am far from the only young scholar to engage in quantitative research, and suspect I that my experience this summer was far from unique. Generous, excellent advice from mentors and colleagues was essential as I navigated my way through court records. But is this kind of informal, ad hoc training enough for historians as we engage in our own counting and as we critique the quantitative research of others?

Even as we have moved away from counting as a principal research strategy, numbers have the power to cultivate trust and admiration in readers. If we are not sufficiently transparent about the decisions associated with counting, we reinforce tendencies to see its methodology as self-evident. Particularly as history’s disciplinary boundaries (or lack thereof) continue to come under scrutiny, I would argue that it is incumbent upon us to talk more openly about the perils and possibilities of quantitative research and to offer historians more formal training in how to count.

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7 responses

Thanks for an interesting post. New technologies drove social science history in the 70s – my teachers used to talk about late nights with punch cards and giant computers. Yet now, when our capacity to process that data has multiplied exponentially, and we have a far vaster dataset at our disposal than anything they had, that kind of scholarship is out of fashion. Have Fogel and Engermann’s sins pushed an entire approach to the margins? I’ve noticed in historiography classes how often Time on the Cross appears as the reading for the session on cliometrics, but we wouldn’t chose a book with so many flaws for sessions on cultural history. Maybe the spatial turn, the surge of interest in historical political economy, and greater literacy in the likes of SPSS and ArcGIS will get us counting again – this time with more awareness of how ostensibly neutral categories are artifacts of a place and time – but I’m not sure how many grad programs provide a training in it. Mine had a number of (mostly recovering) econometricians on the faculty, but for most of us, the stats class was something we took to avoid a second language exam.

Thanks for these reflections, Andrew. I agree that Fogel and Engermann’s work casts a long shadow on quantitative research–in fact, another Juntoist had suggested I mention them in this post. From informal surveying of colleagues in the US, my impression is that few history grad programs offer training in statistics. When they do, it tends to be through other social science departments rather than through in-depth conversations about which statistical methods are appropriate for the oftentimes spotty data sets that are available to historians of the early modern period and nineteenth century.

Sara, it’s great that you’re bringing up these questions. I go through my coursework and qualifying exams without so much as having to think about learning statistics. When I became interested in it myself, I learned a few things. First, my department had once taught stats but, sometime in the eighties, grad students taking the cultural turn lost interest and the class was discontinued. Second, having already gone deeply into my dissertation work, it was a major challenge to pick up quantitative skills that allow for more than just counting, i.e., for mathematically rigorous analysis. After completing my dissertation I did take a grad-level stats class in a sociology department and found it incredibly interesting, but so far I have not found a way to make use of it in my current research. In any event, I wonder whether an article with a regression table would even be readable to most historians today.

Let me echo Andrew and Ariel – it’s great to see quant getting thrown back into the mix. Kudos for a great post.

As someone with formal quantitative training I think it’s important to note that cliometric methods are a means unto an end. History is fundamentally about people, not numbers. One of the reasons why Quant fell out of favor in the 1990s was an increasing focus on minutiae without readily apparent use for the overall big-picture.

One of the key problems of regressions, for example, is that they are used to demonstrate statistically significant evidence of correlation between an independent and a dependent variable. However, correlation is not causation. And, if historians are interested in any one thing it’s “why.” Regressions may get us close to that answer, but they are not an answer in and of themselves. Plus, when we deal with individuals, we’re all too often dealing with an “N” of 1.

Thus, I think you’re spot on when you say that the use (and disuse) of quantitative methods comes from the questions that historians ask of the past. But, it’s also on this point that I’d like to press your analysis a bit:

Counting is great – but why count in the first place? What historical questions will counting legal outcomes/probate records/musket contracts from the War of 1812 answer?

For answering this question I think that Andrew’s point about quantitative analysis for historical political economy is particularly salient. It’s one thing to write about political debates over economic policies, and another thing entirely to show the very real effects of the implementation of those policies. Quant is thus one way to answer the “so what” question.

For my own work I’ve self-consciously tried not to be the guy who just “counts muskets” (and gunpowder, cannon, uniforms, etc…), but rather someone who uses quantitative analysis to make a larger argument about the importance of politics for economic change in early America.

another thing entirely to show the very real effects of the implementation of those policies

Implementation denotes such a variety of shifts across time and space that quantitative analysis seems almost inevitable. Hopefully the “analysis” is a well-crafted tale.

Thanks, Ariel and Andrew.

Andrew, I agree with you that we shouldn’t count simply for the sake of counting. In response to the question of “why count?,” I’d make two additional points. First, since, as you note, history is “about people,” quantitative analysis offers one way to describe the characteristics of the actors whom we’re studying.

Second, I think that quantitative analysis is particularly useful when we are already making implicitly quantitative claims to justify the significance of our research–for instance, when we are arguing that the actors whom we are studying formed a sizable group, or that the phenomenon we are tracking appeared with some regularity. Quantitative research helps us to validate and support these kinds of significance claims. In my own research, I’ve found that that my offhand guestimates about frequency are not necessarily accurate once I’ve sifted through large amounts of data. Counting helps me to fact-check my impressions. (Of course, I’d quickly add that a research topic doesn’t need to concern large groups or a frequently-occurring phenomenon in order to be significant.)

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

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• Knowledge Base

Methodology

• What Is Quantitative Research? | Definition, Uses & Methods

What Is Quantitative Research? | Definition, Uses & Methods

Published on June 12, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Quantitative research is the process of collecting and analyzing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations.

Quantitative research is the opposite of qualitative research , which involves collecting and analyzing non-numerical data (e.g., text, video, or audio).

Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.

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• How has the average temperature changed globally over the last century?
• Does environmental pollution affect the prevalence of honey bees?
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Table of contents

Quantitative research methods, quantitative data analysis, advantages of quantitative research, disadvantages of quantitative research, other interesting articles, frequently asked questions about quantitative research.

You can use quantitative research methods for descriptive, correlational or experimental research.

• In descriptive research , you simply seek an overall summary of your study variables.
• In correlational research , you investigate relationships between your study variables.
• In experimental research , you systematically examine whether there is a cause-and-effect relationship between variables.

Correlational and experimental research can both be used to formally test hypotheses , or predictions, using statistics. The results may be generalized to broader populations based on the sampling method used.

To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).

Note that quantitative research is at risk for certain research biases , including information bias , omitted variable bias , sampling bias , or selection bias . Be sure that you’re aware of potential biases as you collect and analyze your data to prevent them from impacting your work too much.

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Once data is collected, you may need to process it before it can be analyzed. For example, survey and test data may need to be transformed from words to numbers. Then, you can use statistical analysis to answer your research questions .

Descriptive statistics will give you a summary of your data and include measures of averages and variability. You can also use graphs, scatter plots and frequency tables to visualize your data and check for any trends or outliers.

Using inferential statistics , you can make predictions or generalizations based on your data. You can test your hypothesis or use your sample data to estimate the population parameter .

First, you use descriptive statistics to get a summary of the data. You find the mean (average) and the mode (most frequent rating) of procrastination of the two groups, and plot the data to see if there are any outliers.

You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to.

Quantitative research is often used to standardize data collection and generalize findings . Strengths of this approach include:

• Replication

Repeating the study is possible because of standardized data collection protocols and tangible definitions of abstract concepts.

• Direct comparisons of results

The study can be reproduced in other cultural settings, times or with different groups of participants. Results can be compared statistically.

• Large samples

Data from large samples can be processed and analyzed using reliable and consistent procedures through quantitative data analysis.

• Hypothesis testing

Using formalized and established hypothesis testing procedures means that you have to carefully consider and report your research variables, predictions, data collection and testing methods before coming to a conclusion.

Despite the benefits of quantitative research, it is sometimes inadequate in explaining complex research topics. Its limitations include:

• Superficiality

Using precise and restrictive operational definitions may inadequately represent complex concepts. For example, the concept of mood may be represented with just a number in quantitative research, but explained with elaboration in qualitative research.

• Narrow focus

Predetermined variables and measurement procedures can mean that you ignore other relevant observations.

• Structural bias

Despite standardized procedures, structural biases can still affect quantitative research. Missing data , imprecise measurements or inappropriate sampling methods are biases that can lead to the wrong conclusions.

• Lack of context

Quantitative research often uses unnatural settings like laboratories or fails to consider historical and cultural contexts that may affect data collection and results.

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

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

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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Quantitative Research Essay Examples

A quantitative research essay analyzes numerical data in the form of trends, opinions, or efficiency results. This academic writing genre requires you to generalize the figures across a broad group of people and make a relevant conclusion. The possible research methods comprise questionnaires, polls, and surveys, but the results shall be processed with computational techniques and statistics.

For instance, a paper on organized crime in Texas will calculate the number of offenses committed over a given period and compare the findings with the same period in the past.

Below we’ve gathered dozens of quantitative essay examples to help you brainstorm ideas. You will surely find here a couple of papers that meet your needs.

57 Best Quantitative Research Essay Examples

Audit report for the university of alabama system.

• Subjects: Economics Financial Reporting

Decision Making: Starbucks Transformational Experience

• Subjects: Business Case Study
• Words: 2003

Business Problem Matrix and Research Question Hypotheses

• Subjects: Sciences Statistics
• Words: 2058

Asians Seeking U.S. Education

• Subjects: Education Education Theories
• Words: 3014

Facial Feedback Hypothesis

• Subjects: Psychological Principles Psychology
• Words: 2206

User Satisfaction and Service Quality in Academic Libraries: Use of LibQUAL+

• Subjects: Education Education System
• Words: 4019

Demography of Harbor Hills, Austin, TX

• Subjects: Sociological Theories Sociology
• Words: 2050

Predicting Unemployment Rates to Manage Inventory

• Subjects: Business Management
• Words: 2141

Fuel Consumption for Cars Made in the US and Japan

• Subjects: Business Industry

Theoretical Stock Prices

• Subjects: Economics Investment

Supply Chain Design: Honda Gulf

• Words: 2999

Using Smartphones in Learning

• Subjects: Tech & Engineering Technology in Education
• Words: 6084

Action Research in Science Education

• Subjects: Education Writing & Assignments
• Words: 1199

Introduction to Nursing Research

• Subjects: Health & Medicine Healthcare Research

Students’ Perception of a Mobile Application for College Course

• Words: 1500

Carbon Fiber Reinforced Polymer Application

• Subjects: Construction Design
• Words: 1440

An Evaluation of the Suitability of ‘New Headway- Intermediate’ by Liz & John Soars

• Subjects: Education Pedagogical Approaches
• Words: 3456

Parenting Variables in Antenatal Education

• Subjects: Family Planning Health & Medicine
• Words: 1211

Sustained Organisational Learning Methods

• Words: 1416

The Achievement of Millennium Development Goals in India

• Subjects: International Relations Politics & Government

The EV Products in China

• Words: 1146

Green Energy Brand Strategy: Chinese E-Car Consumer Behaviour

• Subjects: Business Strategy
• Words: 3378

Binomial Logistic Regression

• Subjects: Math Sciences

Odds Ratio in Logistic Regression

Efficacy of antibiotic therapy and appendectomy, local food production in malaysia.

• Words: 1625

The Indian Agriculture Sector

• Subjects: Agriculture Sciences
• Words: 1662

Beer Market Trends in the UK

• Subjects: Business Marketing
• Words: 1374

Waste Management in Australia

• Subjects: Environment Recycling
• Words: 1851

Health and Environment in Abu Dhabi

• Subjects: Air Pollution Environment
• Words: 3126

The Relations Between Media and School Violence

• Subjects: Sociology Violence
• Words: 2832

BlackBerry Management Perspectives

• Words: 2831

Apple Inc. Equity Valuation

• Words: 3729

Zara Fashions’ Supply Chain

• Words: 6066

The Extent to Which FDI Inflows have Influenced GDPGrowth in India

• Subjects: Economic Trends Economics
• Words: 1780

Addicted 2 Football Business Plan

• Subjects: Business Company Analysis
• Words: 2514

Ashtead Group Plc Financial Accounting

• Words: 5733

Reaching the Critical Mass in eMarketplaces

• Subjects: Business E-Commerce
• Words: 2204

Independent Samples t-test with SPSS

Economics concepts: alfred marshall.

• Subjects: Economic Concepts Economics

Exploring Reliability and Validity

• Subjects: Psychological Issues Psychology

Sustaining Australia’s Rate of Economic Growth

• Subjects: Economic Systems & Principles Economics
• Words: 1356

E-Cig Project and Price Customization

• Subjects: Business Marketing Project

Public Relations and Customer Loyalty

• Subjects: Branding Business
• Words: 2118

Game-based Learning and Simulation in a K-12 School in the United Arab Emirates

• Subjects: Education Pedagogy
• Words: 3683

The Issue of Muslims’ Immigration to Australia

• Subjects: Immigration Sociology
• Words: 3492

China’s Energy and Environmental Implications

• Subjects: Ecology Environment
• Words: 3709

The Target Company

• Words: 4066

The Effect of Social Media on Today’s Youth

• Subjects: Entertainment & Media Social Media Issues
• Words: 2165

Heineken Company in the US market

• Words: 1275

International Communication in Saudi Arabia

• Subjects: Communications Sociology
• Words: 1390

The Algerian Wool Company

• Words: 2570

Jewish Life in North America

• Subjects: Sociological Issues Sociology
• Words: 1788

Impact of Gambling on the Bahamian Economy

• Subjects: Economics Influences on Political Economy
• Words: 3871

International Marketing Plan for Tata Nano

• Subjects: Business Financial Marketing
• Words: 5299

Home Based and Community Based Services (HCBS)

• Subjects: Health & Medicine Healthcare Institution

Case of Ski Pro Corporation

• Subjects: Business Company Missions

Personal Reflection Sample: preparing a Research Report for ACCA

The skill and learning statement includes the implications of interactions with mentor, an analysis of the extent to which research questions have been answered, a brief analysis of interpersonal and communication skills and their relevance to the research, as well as the contribution of the research experience to my professional and personal development.

1.      Experiences of interactions with mentor

I had chances of meeting my project mentor three times and obtained practical support regarding various aspects of the work during these meetings. Our first meeting was mainly dedicated to clarifying our expectations from the research experience and the discussions took place related to the issues of selection of the research approach and formulation of research questions and objectives.

By the time I had a meeting with my mentor for the second time Introduction and Information gathering chapters of the work have been completed and I received detailed feedback for these chapters of the research. Also, discussions were held about data analysis and presentation associated with the project.

During the final meeting with my mentor the overall work has been scrutinised and a set of specific points have been mentioned by my mentor. Specifically, my mentor raised a point that my discussions of research findings lacked depth and scale. Then, these points have been addressed and the final draft of the Research Report was completed.

I found advices given by my mentor very helpful in terms of increasing the quality of my Research Report and equipping me with knowledge of effectively conducting similar studies in the future in general. Moreover, my Project Mentor was not only highlighting the shortages that were associated with my project, but also was giving detailed explanations why these changes were desirable in a passionate manner.

Furthermore, I found these three sessions with my mentor to be highly motivational and informative experience because they have increased the level of my personal interest in conducting businesses studies. Prior to conducting the Research Report and having discussions with my mentor I was assuming conducting analytical business studies to be a rather boring experience.

However, thanks to my mentor I learned to appreciate the importance of analysing a business case in terms of identifying a current strategic and financial position of a business, and formulating the ways of identifying further strategic options available to the business.

2.      The extent to which research questions have been answered

Answering the research questions in my Research Report were directly related to the quality of secondary data, and the choice of methodology. Therefore, these issues were approached effectively by critically assessing the validity of the sources of secondary data and assessing alternative choices of methodology. Moreover, my first meeting with my Project mentor was mainly devoted to the discussion of the same issues.

As a result of comprehensive analysis the most reliable sources of secondary data in order to be used in Research Report were found to include published financial statements and annual reports, textbooks on financial and business analysis, information published in official company website, information available from ACCA website, as well as, various business journals an newspapers.

The choice of methods for conducting the study, on the other hand, was guided by the reliability of the data analysis methods and their relevance to the research issues. After spending additional amount of time for the choice of appropriate methodology and taking into account advises of my mentor, financial ratios and analytic tools have been chosen to be employed in my Research Report.

Purposely, financial and accounting ratios that were used in the study include profitability, liquidity, financial position and investor ratios, whereas, the choice of analytic tools consist of SWOT, PESTLE, and Porter’s five forces analysis.

To summarise this part, it is fair to state that all of the research questions in my Research Report have been effectively addressed, because the secondary data have been obtained from reliable sources, relevant methodology has been used to conduct the study, and the research findings have been critically discussed.

3.      Interpersonal and communication skills and their relevance to the research

I have demonstrated my interpersonal and communication skills at various stages of doing Research Report and preparing for and making the presentation. Moreover, without my interpersonal and communication skills completing the Research Report and doing the presentation would have proved to be highly challenging.

For example, my listening skills have proved to be highly valuable in terms of understanding vital information given by my mentor about increasing the quality of my Research Report, because these advises were fully understood and implemented into the practice.

My interpersonal skills have also played a positive role when I asked some of my trusted colleagues to be an audience when I was rehearsing my presentation. I was making presentations in front of my colleagues and was asking for their opinions about the quality of my presentation. This practice took place many times in different settings and I believe that following this strategy has enhanced the quality of my presentation and my marks.

However, my communication skills have played a crucial role in terms of succeeding in making the presentation effectively. I have learned from my experiences within and outside of academic settings that communication skills play the most crucial role in terms of succeeding in personal and professional lives.

For instance, an individual may possess a deep knowledge about a certain area. However, if the individual lacks competency of communicating his or her ideas, knowledge and feelings in an effective manner, the overall competency of the individual and the level of his or her contribution to the organisation will always remain compromised.

Therefore, in my opinion, regardless of the field, industry or type of organisation, communication skills can be specified as a compulsory attribute for an employee in order to be considered an a competent. In my case in particular, my advanced level of communication skills have enabled me to do my Research Report presentation effectively which has resulted in positive acclaim from my peers and mentor.

4.      The potential contribution of Research Report to the level of professional development

Conducting the Research Report and doing the presentation has increased the level of my professional competency in several ways. First of all, I have to mention the fact that I have developed a critical mindset towards solving business issues as a result of conducting the Research Report.

My mentor made it clear that it was important to critically analyse related issues in Research Report rather than just offering description of the issues and supplying calculations. The mentor had stressed many times that critical analysis and discussions are the elements of the work that increase its value. For the same reason I had to revise my Research Report several times until my mentor was satisfied with the level of critical analysis the work had included.

Although, such an approach to work seemed to be very challenging and confusing during the research process, I appreciated the value of critical analysis once the final work was completed. The skills of critical analysis that I have developed and applied in Research Report can easily be applied when real business issues would need to be resolved by me in the future in my professional capacity.

Completing the Research Report was similar to project management in real businesses environment in terms of strict deadlines, scarcity of resources, organising and planning, scheduling meetings, doing presentations etc. Therefore, the skills I developed during the process of completing Research Report can be used in order to successfully manage business projects in the future.

Moreover, my writing skills have also been greatly improved as a result of engaging in Research Report. Despite the popular opinion that with the increasing importance of information technology the practice of writing letters and reports are being replaced by alternative means of business communications, the importance of writing will always remain significant for business managers.

From this point of view engaging in Research Report was a very beneficial experience for me on a personal level. Specifically, writing the paper of almost ten thousand words in total, including this personal reflection, has made me better prepared to join the full-time workforce once my studies are completed.

Lastly, as a result of preparing the Research Report my professional interest on the issues associated with corporate strategy has been enhanced. Moreover, I am planning to continue studying the issues of corporate strategy and that knowledge would benefit me in the future as a corporate leader.

5.      Gains derived from conducting Research Report experience on a personal level

On a personal level I benefited from conducting the Research Report and doing the presentation in a number of ways. The research experience with Oxford Brookes has increased the level of my motivation for studying, making bold plans for my future career and implements necessary measures and initiatives in order to accomplish these plans. My mentor deserves to be mentioned here specifically for all encouragements and practical tips that can be applied in various alternative settings apart from academic life.

The level of my self-confidence has also been increased because I could complete the Research Report in time. Moreover, the presentation experience has increased the level of my self-confidence dramatically, because I understood that if I could do a successful presentation in front of my mentor and colleagues, doing the presentations of multi-million projects in front of top executives was just a matter of time.

The paramount importance of self-confidence for an individual is an undisputable matter. Self-confidence allows us to set ambitious plans and utilise all the available resources efficiently in order to achieve these plans.

My time-management skills have also been improved by the end of the Research Report. This is because there was a specific deadline for both, the Research Report and presentation and I had to adopt some principles related to time management in order to be able to submit my work on time.

These principles included setting specific deadlines for each chapter of the work, and above all, dramatically cutting the amount of time I used to browse social networking sites on the internet. I can highlight this fact as one of the most substantial gains in a personal level. This is because prior to the research experience I used to spend several hours a day browsing a set of social networking sites with no real benefit whatsoever. However, once the priority was given to the Research Project, this bad habit was dealt with effectively and irreversibly.

6.      Conclusions

To summarise, completing the Research Report and making presentation with Oxford Brookes University following my ACCA course has increased the level of my preparedness to join the full-time workforce and successfully utilise my energy and knowledge. In my opinion the biggest benefit I received from enrolling to this course of study is that the course of study, the Research Report and doing the presentation have made me to believe in my skills and capabilities and they have also awoke my desire to approach studying as a lifelong process.

Moreover, I have obtained a set of professional and personal gains as a result of completing the Research Report and making presentation that include the development of a critical mindset, improvement my writing and time management skills and enhancement of the level of my self-confidence.

Essay on Qualitative vs. Quantitative Research

Both qualitative and quantitative researches are valued in the research world and are often used together under a single project. This is despite the fact that they have significant differences in terms of their theoretical, epistemological, and methodological formations. Qualitative research is usually in form of words while quantitative research takes the numerical approach. This paper discusses the similarities, differences, advantages, and disadvantages of qualitative and quantitative research and provides a personal stand.

Similarities

Both qualitative and quantitative research approaches begin with a problem on which scholars seek to find answers. Without a research problem or question, there would be no reason for carrying out the study. Once a problem is formulated, researchers at their own discretion and depending on the nature of the question choose the appropriate type of research to employ. Just like in qualitative research, data obtained from quantitative analysis need to be analyzed (Miles & Huberman, 1994). This step is crucial for helping researchers to gain a deeper understanding of the issue under investigation. The findings of any research enjoy confirmability after undergoing a thorough examination and auditing process (Miles & Huberman, 1994).

Both types of research approaches require a concise plan before they are carried out. Once researchers formulate the study question, they must come up with a plan for investigating the matter (Yilmaz, 2013). Such plans include deciding the appropriate research technique to implement, estimating budgets, and deciding on the study areas. Failure to plan before embarking on the research project may compromise the research findings. In addition, both qualitative and quantitative research are dependent on each other and can be used for a single research project (Miles & Huberman, 1994). Quantitative data helps the qualitative research in finding a representative study sample and obtaining the background data. In the same way, qualitative research provides the quantitative side with the conceptual development and instrumentation (Miles & Huberman, 1994).

Differences

Qualitative research seeks to explain why things are the way they seem to be. It provides well-grounded descriptions and explanations of processes in identifiable local contexts (Miles & Huberman, 1994). Researchers use qualitative research to dig deeper into the problem and develop a relevant hypothesis for potential quantitative research. On the other hand, Quantitative research uses numerical data to state and quantify the problem (Yilmaz, 2013). Researchers in quantitative research use measurable data in formulating facts and uncovering the research pattern.

Quantitative research approach involves a larger number of participants for the purpose of gathering as much information as possible to summarize characteristics across large groups. This makes it a very expensive research approach. On the contrary, qualitative research approach describes a phenomenon in a more comprehensive manner. A relatively small number of participants take part in this type of research. This makes the overall process cheaper and time friendly.

Data collection methods differ significantly in the two research approaches. In quantitative research, scholars use surveys, questionnaires, and systematic measurements that involve numbers (Yilmaz, 2013). Moreover, they report their findings in impersonal third person prose by using numbers. This is different from the qualitative approach where only the participants’ observation and deep document analysis is necessary for conclusions to be drawn. Findings are disseminated in the first person’s narrative with sufficient quotations from the participants.

Advantages and Disadvantages of Qualitative Research

Qualitative data is based on human observations. Respondent’s observations connect the researcher to the most basic human experiences (Rahman, 2016). It gives a detailed production of participants’ opinions and feelings and helps in efficient interpretation of their actions (Miles & Huberman, 1994). Moreover, this research approach is interdisciplinary and entails a wide range of research techniques and epistemological viewpoints. Data collection methods in qualitative approach are both detailed and subjective (Rahman, 2016). Direct observations, unstructured interviews, and participant observation are the most common techniques employed in this type of research. Researchers have the opportunity to mingle directly with the respondents and obtain first-hand information.

On the negative side, the smaller population sample used in qualitative research raises credibility concerns (Rahman, 2016). The views of a small group of respondents may not necessarily reflect those of the entire population. Moreover, conducting this type of research on certain aspects such as the performance of students may be more challenging. In such instances, researchers prefer to use the quantitative approach instead (Rahman, 2016). Data analysis and interpretation in qualitative research is a more complex process. It is long, has elusive data, and has very stringent requirements for analysis (Rahman, 2016). In addition, developing a research question in this approach is a challenging task as the refining question mostly becomes continuous throughout the research process.

Advantages and Disadvantages of Quantitative Research

The findings of a quantitative research can be generalized to a whole population as it involves larger samples that are randomly selected by researchers (Rahman, 2016). Moreover, the methods used allows for use of statistical software in test taking (Rahman, 2016). This makes the approach time effective and efficient for tackling complex research questions. Quantitative research allows for objectivity and accuracy of the study results. This approach is well designed to provide essential information that supports generalization of a phenomenon under study. It involves few variables and many cases that guarantee the validity and credibility of the study results.

This research approach, however, has some limitations. There is a limited direct connection between the researcher and respondents. Scholars who adopt this approach measure variables at specific moments in time and disregards the past experiences of the respondents (Rahman, 2016). As a result, deep information is often ignored and only the overall picture of the variables is represented. The quantitative approach uses standard questions set and administered by researchers (Rahman, 2016). This might lead to structural bias by respondents and false representation. In some instances, data may only reflect the views of the sample under study instead of revealing the real situation. Moreover, preset questions and answers limit the freedom of expression by the respondents.

Preferred Method

I would prefer quantitative research method over the qualitative approach. Data management in this technique is much familiar and more accessible to researchers’ contexts (Miles & Huberman, 1994). It is a more scientific process that involves the collection, analysis, and interpretation of large amounts of data. Researchers have more control of the manner in which data is collected. Unlike qualitative data that requires descriptions, quantitative approach majors on numerical data (Yilmaz, 2013). With this type of data, I can use the various available software for classification and analyzes. Moreover, researchers are more flexible and free to interact with respondents. This gives an opportunity for obtaining first-hand information and learning more about other behavioral aspects of the population under study.

As highlighted above, qualitative and quantitative techniques are the two research approaches. Both seek to dig deeper into a particular problem, analyze the responses of a selected sample and make viable conclusions. However, qualitative research is much concerned with the description of peoples’ opinions, motivations, and reasons for a particular phenomenon. On the other hand, Quantitative research uses numerical data to state and explain research findings. Use of numerical data allows for objectivity and accuracy of the research results. However structural biases are common in this approach. Data collection and sampling in qualitative research is more detailed and subjective. Considering the different advantages and disadvantages of the two research approaches, I would go for the quantitative over qualitative research.

Miles, M., & Huberman, A. (1994).  Qualitative data analysis  (2nd Ed.). Beverly Hills: Sage.

Rahman, M. (2016). The Advantages and Disadvantages of Using Qualitative and Quantitative Approaches and Methods in Language “Testing and Assessment” Research: A Literature Review.  Journal of Education and Learning , 6(1), 102.

Yilmaz, K. (2013). Comparison of Quantitative and Qualitative Research Traditions: epistemological, theoretical, and methodological differences.  European Journal of Education , 48(2), 311-325.

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Home — Essay Samples — Science — Quantitative Research — Qualitative Vs. Quantitative Research

Difference Between Qualitative and Quantitative Research

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Words: 1594 |

Published: Mar 14, 2019

Words: 1594 | Pages: 4 | 8 min read

Table of contents

Introduction, compare and contrast: qualitative and quantitative research, works cited.

• Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Sage Publications.
• Denzin, N. K., & Lincoln, Y. S. (Eds.). (2018). The SAGE handbook of qualitative research (5th ed.). Sage Publications.
• Neuman, W. L. (2014). Social research methods: Qualitative and quantitative approaches (7th ed.). Pearson.
• Palys, T., & Atchison, C. (2018). Qualitative research in the digital era: Obstacles and opportunities. International Journal of Qualitative Methods, 17(1), 1-11. https://doi.org/10.1177/1609406918813901
• Maxwell, J. A. (2013). Qualitative research design: An interactive approach (3rd ed.). Sage Publications.
• Bryman, A. (2016). Social research methods (5th ed.). Oxford University Press.
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• Morgan, D. L. (2013). Integrating qualitative and quantitative methods: A pragmatic approach. Sage Publications.

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