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Writing a Rsearch Proposal

A research proposal describes what you will investigate, why it’s important, and how you will conduct your research. Your paper should include the topic, research question and hypothesis, methods, predictions, and results (if not actual, then projected).

Research Proposal Aims

The format of a research proposal varies between fields, but most proposals will contain at least these elements:

Introduction

Literature review

Research design

Reference list

While the sections may vary, the overall objective is always the same. A research proposal serves as a blueprint and guide for your research plan, helping you get organized and feel confident in the path forward you choose to take.

Proposal Format

The proposal will usually have a title page that includes:

The proposed title of your project
Your supervisor’s name
Your institution and department

Introduction The first part of your proposal is the initial pitch for your project. Make sure it succinctly explains what you want to do and why.. Your introduction should:

Introduce your topic
Give necessary background and context
Outline your problem statement and research questions To guide your introduction , include information about:
Who could have an interest in the topic (e.g., scientists, policymakers)
How much is already known about the topic
What is missing from this current knowledge
What new insights will your research contribute
Why you believe this research is worth doing

As you get started, it’s important to demonstrate that you’re familiar with the most important research on your topic. A strong literature review shows your reader that your project has a solid foundation in existing knowledge or theory. It also shows that you’re not simply repeating what other people have done or said, but rather using existing research as a jumping-off point for your own.

In this section, share exactly how your project will contribute to ongoing conversations in the field by:

Comparing and contrasting the main theories, methods, and debates
Examining the strengths and weaknesses of different approaches
Explaining how will you build on, challenge, or synthesize prior scholarship

Research design and methods

Following the literature review, restate your main objectives . This brings the focus back to your project. Next, your research design or methodology section will describe your overall approach, and the practical steps you will take to answer your research questions. Write up your projected, if not actual, results.

Contribution to knowledge

To finish your proposal on a strong note, explore the potential implications of your research for your field. Emphasize again what you aim to contribute and why it matters.

For example, your results might have implications for:

Improving best practices
Informing policymaking decisions
Strengthening a theory or model
Challenging popular or scientific beliefs
Creating a basis for future research

Lastly, your research proposal must include correct citations for every source you have used, compiled in a reference list . To create citations quickly and easily, you can use free APA citation generators like BibGuru. Databases have a citation button you can click on to see your citation. Sometimes you have to re-format it as the citations may have mistakes.

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Organizing Your Social Sciences Research Assignments

Annotated Bibliography
Analyzing a Scholarly Journal Article
Group Presentations
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Types of Structured Group Activities
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Writing a Research Proposal
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Acknowledgments

The goal of a research proposal is twofold: to present and justify the need to study a research problem and to present the practical ways in which the proposed study should be conducted. The design elements and procedures for conducting research are governed by standards of the predominant discipline in which the problem resides, therefore, the guidelines for research proposals are more exacting and less formal than a general project proposal. Research proposals contain extensive literature reviews. They must provide persuasive evidence that a need exists for the proposed study. In addition to providing a rationale, a proposal describes detailed methodology for conducting the research consistent with requirements of the professional or academic field and a statement on anticipated outcomes and benefits derived from the study's completion.

Krathwohl, David R. How to Prepare a Dissertation Proposal: Suggestions for Students in Education and the Social and Behavioral Sciences . Syracuse, NY: Syracuse University Press, 2005.

How to Approach Writing a Research Proposal

Your professor may assign the task of writing a research proposal for the following reasons:

Develop your skills in thinking about and designing a comprehensive research study;
Learn how to conduct a comprehensive review of the literature to determine that the research problem has not been adequately addressed or has been answered ineffectively and, in so doing, become better at locating pertinent scholarship related to your topic;
Improve your general research and writing skills;
Practice identifying the logical steps that must be taken to accomplish one's research goals;
Critically review, examine, and consider the use of different methods for gathering and analyzing data related to the research problem; and,
Nurture a sense of inquisitiveness within yourself and to help see yourself as an active participant in the process of conducting scholarly research.

A proposal should contain all the key elements involved in designing a completed research study, with sufficient information that allows readers to assess the validity and usefulness of your proposed study. The only elements missing from a research proposal are the findings of the study and your analysis of those findings. Finally, an effective proposal is judged on the quality of your writing and, therefore, it is important that your proposal is coherent, clear, and compelling.

Regardless of the research problem you are investigating and the methodology you choose, all research proposals must address the following questions:

What do you plan to accomplish? Be clear and succinct in defining the research problem and what it is you are proposing to investigate.
Why do you want to do the research? In addition to detailing your research design, you also must conduct a thorough review of the literature and provide convincing evidence that it is a topic worthy of in-depth study. A successful research proposal must answer the "So What?" question.
How are you going to conduct the research? Be sure that what you propose is doable. If you're having difficulty formulating a research problem to propose investigating, go here for strategies in developing a problem to study.

Common Mistakes to Avoid

Failure to be concise . A research proposal must be focused and not be "all over the map" or diverge into unrelated tangents without a clear sense of purpose.
Failure to cite landmark works in your literature review . Proposals should be grounded in foundational research that lays a foundation for understanding the development and scope of the the topic and its relevance.
Failure to delimit the contextual scope of your research [e.g., time, place, people, etc.]. As with any research paper, your proposed study must inform the reader how and in what ways the study will frame the problem.
Failure to develop a coherent and persuasive argument for the proposed research . This is critical. In many workplace settings, the research proposal is a formal document intended to argue for why a study should be funded.
Sloppy or imprecise writing, or poor grammar . Although a research proposal does not represent a completed research study, there is still an expectation that it is well-written and follows the style and rules of good academic writing.
Too much detail on minor issues, but not enough detail on major issues . Your proposal should focus on only a few key research questions in order to support the argument that the research needs to be conducted. Minor issues, even if valid, can be mentioned but they should not dominate the overall narrative.

Procter, Margaret. The Academic Proposal. The Lab Report. University College Writing Centre. University of Toronto; Sanford, Keith. Information for Students: Writing a Research Proposal. Baylor University; Wong, Paul T. P. How to Write a Research Proposal. International Network on Personal Meaning. Trinity Western University; Writing Academic Proposals: Conferences, Articles, and Books. The Writing Lab and The OWL. Purdue University; Writing a Research Proposal. University Library. University of Illinois at Urbana-Champaign.

Structure and Writing Style

Beginning the Proposal Process

As with writing most college-level academic papers, research proposals are generally organized the same way throughout most social science disciplines. The text of proposals generally vary in length between ten and thirty-five pages, followed by the list of references. However, before you begin, read the assignment carefully and, if anything seems unclear, ask your professor whether there are any specific requirements for organizing and writing the proposal.

A good place to begin is to ask yourself a series of questions:

What do I want to study?
Why is the topic important?
How is it significant within the subject areas covered in my class?
What problems will it help solve?
How does it build upon [and hopefully go beyond] research already conducted on the topic?
What exactly should I plan to do, and can I get it done in the time available?

In general, a compelling research proposal should document your knowledge of the topic and demonstrate your enthusiasm for conducting the study. Approach it with the intention of leaving your readers feeling like, "Wow, that's an exciting idea and I can’t wait to see how it turns out!"

Most proposals should include the following sections:

I. Introduction

In the real world of higher education, a research proposal is most often written by scholars seeking grant funding for a research project or it's the first step in getting approval to write a doctoral dissertation. Even if this is just a course assignment, treat your introduction as the initial pitch of an idea based on a thorough examination of the significance of a research problem. After reading the introduction, your readers should not only have an understanding of what you want to do, but they should also be able to gain a sense of your passion for the topic and to be excited about the study's possible outcomes. Note that most proposals do not include an abstract [summary] before the introduction.

Think about your introduction as a narrative written in two to four paragraphs that succinctly answers the following four questions :

What is the central research problem?
What is the topic of study related to that research problem?
What methods should be used to analyze the research problem?
Answer the "So What?" question by explaining why this is important research, what is its significance, and why should someone reading the proposal care about the outcomes of the proposed study?

II. Background and Significance

This is where you explain the scope and context of your proposal and describe in detail why it's important. It can be melded into your introduction or you can create a separate section to help with the organization and narrative flow of your proposal. Approach writing this section with the thought that you can’t assume your readers will know as much about the research problem as you do. Note that this section is not an essay going over everything you have learned about the topic; instead, you must choose what is most relevant in explaining the aims of your research.

To that end, while there are no prescribed rules for establishing the significance of your proposed study, you should attempt to address some or all of the following:

State the research problem and give a more detailed explanation about the purpose of the study than what you stated in the introduction. This is particularly important if the problem is complex or multifaceted .
Present the rationale of your proposed study and clearly indicate why it is worth doing; be sure to answer the "So What? question [i.e., why should anyone care?].
Describe the major issues or problems examined by your research. This can be in the form of questions to be addressed. Be sure to note how your proposed study builds on previous assumptions about the research problem.
Explain the methods you plan to use for conducting your research. Clearly identify the key sources you intend to use and explain how they will contribute to your analysis of the topic.
Describe the boundaries of your proposed research in order to provide a clear focus. Where appropriate, state not only what you plan to study, but what aspects of the research problem will be excluded from the study.
If necessary, provide definitions of key concepts, theories, or terms.

III. Literature Review

Connected to the background and significance of your study is a section of your proposal devoted to a more deliberate review and synthesis of prior studies related to the research problem under investigation . The purpose here is to place your project within the larger whole of what is currently being explored, while at the same time, demonstrating to your readers that your work is original and innovative. Think about what questions other researchers have asked, what methodological approaches they have used, and what is your understanding of their findings and, when stated, their recommendations. Also pay attention to any suggestions for further research.

Since a literature review is information dense, it is crucial that this section is intelligently structured to enable a reader to grasp the key arguments underpinning your proposed study in relation to the arguments put forth by other researchers. A good strategy is to break the literature into "conceptual categories" [themes] rather than systematically or chronologically describing groups of materials one at a time. Note that conceptual categories generally reveal themselves after you have read most of the pertinent literature on your topic so adding new categories is an on-going process of discovery as you review more studies. How do you know you've covered the key conceptual categories underlying the research literature? Generally, you can have confidence that all of the significant conceptual categories have been identified if you start to see repetition in the conclusions or recommendations that are being made.

NOTE: Do not shy away from challenging the conclusions made in prior research as a basis for supporting the need for your proposal. Assess what you believe is missing and state how previous research has failed to adequately examine the issue that your study addresses. Highlighting the problematic conclusions strengthens your proposal. For more information on writing literature reviews, GO HERE .

To help frame your proposal's review of prior research, consider the "five C’s" of writing a literature review:

Cite , so as to keep the primary focus on the literature pertinent to your research problem.
Compare the various arguments, theories, methodologies, and findings expressed in the literature: what do the authors agree on? Who applies similar approaches to analyzing the research problem?
Contrast the various arguments, themes, methodologies, approaches, and controversies expressed in the literature: describe what are the major areas of disagreement, controversy, or debate among scholars?
Critique the literature: Which arguments are more persuasive, and why? Which approaches, findings, and methodologies seem most reliable, valid, or appropriate, and why? Pay attention to the verbs you use to describe what an author says/does [e.g., asserts, demonstrates, argues, etc.].
Connect the literature to your own area of research and investigation: how does your own work draw upon, depart from, synthesize, or add a new perspective to what has been said in the literature?

IV. Research Design and Methods

This section must be well-written and logically organized because you are not actually doing the research, yet, your reader must have confidence that you have a plan worth pursuing . The reader will never have a study outcome from which to evaluate whether your methodological choices were the correct ones. Thus, the objective here is to convince the reader that your overall research design and proposed methods of analysis will correctly address the problem and that the methods will provide the means to effectively interpret the potential results. Your design and methods should be unmistakably tied to the specific aims of your study.

Describe the overall research design by building upon and drawing examples from your review of the literature. Consider not only methods that other researchers have used, but methods of data gathering that have not been used but perhaps could be. Be specific about the methodological approaches you plan to undertake to obtain information, the techniques you would use to analyze the data, and the tests of external validity to which you commit yourself [i.e., the trustworthiness by which you can generalize from your study to other people, places, events, and/or periods of time].

When describing the methods you will use, be sure to cover the following:

Specify the research process you will undertake and the way you will interpret the results obtained in relation to the research problem. Don't just describe what you intend to achieve from applying the methods you choose, but state how you will spend your time while applying these methods [e.g., coding text from interviews to find statements about the need to change school curriculum; running a regression to determine if there is a relationship between campaign advertising on social media sites and election outcomes in Europe ].
Keep in mind that the methodology is not just a list of tasks; it is a deliberate argument as to why techniques for gathering information add up to the best way to investigate the research problem. This is an important point because the mere listing of tasks to be performed does not demonstrate that, collectively, they effectively address the research problem. Be sure you clearly explain this.
Anticipate and acknowledge any potential barriers and pitfalls in carrying out your research design and explain how you plan to address them. No method applied to research in the social and behavioral sciences is perfect, so you need to describe where you believe challenges may exist in obtaining data or accessing information. It's always better to acknowledge this than to have it brought up by your professor!

V. Preliminary Suppositions and Implications

Just because you don't have to actually conduct the study and analyze the results, doesn't mean you can skip talking about the analytical process and potential implications . The purpose of this section is to argue how and in what ways you believe your research will refine, revise, or extend existing knowledge in the subject area under investigation. Depending on the aims and objectives of your study, describe how the anticipated results will impact future scholarly research, theory, practice, forms of interventions, or policy making. Note that such discussions may have either substantive [a potential new policy], theoretical [a potential new understanding], or methodological [a potential new way of analyzing] significance. When thinking about the potential implications of your study, ask the following questions:

What might the results mean in regards to challenging the theoretical framework and underlying assumptions that support the study?
What suggestions for subsequent research could arise from the potential outcomes of the study?
What will the results mean to practitioners in the natural settings of their workplace, organization, or community?
Will the results influence programs, methods, and/or forms of intervention?
How might the results contribute to the solution of social, economic, or other types of problems?
Will the results influence policy decisions?
In what way do individuals or groups benefit should your study be pursued?
What will be improved or changed as a result of the proposed research?
How will the results of the study be implemented and what innovations or transformative insights could emerge from the process of implementation?

NOTE: This section should not delve into idle speculation, opinion, or be formulated on the basis of unclear evidence . The purpose is to reflect upon gaps or understudied areas of the current literature and describe how your proposed research contributes to a new understanding of the research problem should the study be implemented as designed.

ANOTHER NOTE : This section is also where you describe any potential limitations to your proposed study. While it is impossible to highlight all potential limitations because the study has yet to be conducted, you still must tell the reader where and in what form impediments may arise and how you plan to address them.

VI. Conclusion

The conclusion reiterates the importance or significance of your proposal and provides a brief summary of the entire study . This section should be only one or two paragraphs long, emphasizing why the research problem is worth investigating, why your research study is unique, and how it should advance existing knowledge.

Someone reading this section should come away with an understanding of:

Why the study should be done;
The specific purpose of the study and the research questions it attempts to answer;
The decision for why the research design and methods used where chosen over other options;
The potential implications emerging from your proposed study of the research problem; and
A sense of how your study fits within the broader scholarship about the research problem.

VII. Citations

As with any scholarly research paper, you must cite the sources you used . In a standard research proposal, this section can take two forms, so consult with your professor about which one is preferred.

References -- a list of only the sources you actually used in creating your proposal.
Bibliography -- a list of everything you used in creating your proposal, along with additional citations to any key sources relevant to understanding the research problem.

In either case, this section should testify to the fact that you did enough preparatory work to ensure the project will complement and not just duplicate the efforts of other researchers. It demonstrates to the reader that you have a thorough understanding of prior research on the topic.

Most proposal formats have you start a new page and use the heading "References" or "Bibliography" centered at the top of the page. Cited works should always use a standard format that follows the writing style advised by the discipline of your course [e.g., education=APA; history=Chicago] or that is preferred by your professor. This section normally does not count towards the total page length of your research proposal.

Develop a Research Proposal: Writing the Proposal. Office of Library Information Services. Baltimore County Public Schools; Heath, M. Teresa Pereira and Caroline Tynan. “Crafting a Research Proposal.” The Marketing Review 10 (Summer 2010): 147-168; Jones, Mark. “Writing a Research Proposal.” In MasterClass in Geography Education: Transforming Teaching and Learning . Graham Butt, editor. (New York: Bloomsbury Academic, 2015), pp. 113-127; Juni, Muhamad Hanafiah. “Writing a Research Proposal.” International Journal of Public Health and Clinical Sciences 1 (September/October 2014): 229-240; Krathwohl, David R. How to Prepare a Dissertation Proposal: Suggestions for Students in Education and the Social and Behavioral Sciences . Syracuse, NY: Syracuse University Press, 2005; Procter, Margaret. The Academic Proposal. The Lab Report. University College Writing Centre. University of Toronto; Punch, Keith and Wayne McGowan. "Developing and Writing a Research Proposal." In From Postgraduate to Social Scientist: A Guide to Key Skills . Nigel Gilbert, ed. (Thousand Oaks, CA: Sage, 2006), 59-81; Wong, Paul T. P. How to Write a Research Proposal. International Network on Personal Meaning. Trinity Western University; Writing Academic Proposals: Conferences , Articles, and Books. The Writing Lab and The OWL. Purdue University; Writing a Research Proposal. University Library. University of Illinois at Urbana-Champaign.

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Writing the Data Analysis Plan

First Online: 01 January 2010

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You and your project statistician have one major goal for your data analysis plan: You need to convince all the reviewers reading your proposal that you would know what to do with your data once your project is funded and your data are in hand. The data analytic plan is a signal to the reviewers about your ability to score, describe, and thoughtfully synthesize a large number of variables into appropriately-selected quantitative models once the data are collected. Reviewers respond very well to plans with a clear elucidation of the data analysis steps – in an appropriate order, with an appropriate level of detail and reference to relevant literatures, and with statistical models and methods for that map well into your proposed aims. A successful data analysis plan produces reviews that either include no comments about the data analysis plan or better yet, compliments it for being comprehensive and logical given your aims. This chapter offers practical advice about developing and writing a compelling, “bullet-proof” data analytic plan for your grant application.

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Panter, A.T. (2010). Writing the Data Analysis Plan. In: Pequegnat, W., Stover, E., Boyce, C. (eds) How to Write a Successful Research Grant Application. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1454-5_22

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Data Analysis in Research: Types & Methods

Content Index

Why analyze data in research?

Types of data in research, finding patterns in the qualitative data, methods used for data analysis in qualitative research, preparing data for analysis, methods used for data analysis in quantitative research, considerations in research data analysis, what is data analysis in research.

Definition of research in data analysis: According to LeCompte and Schensul, research data analysis is a process used by researchers to reduce data to a story and interpret it to derive insights. The data analysis process helps reduce a large chunk of data into smaller fragments, which makes sense.

Three essential things occur during the data analysis process — the first is data organization . Summarization and categorization together contribute to becoming the second known method used for data reduction. It helps find patterns and themes in the data for easy identification and linking. The third and last way is data analysis – researchers do it in both top-down and bottom-up fashion.

LEARN ABOUT: Research Process Steps

On the other hand, Marshall and Rossman describe data analysis as a messy, ambiguous, and time-consuming but creative and fascinating process through which a mass of collected data is brought to order, structure and meaning.

We can say that “the data analysis and data interpretation is a process representing the application of deductive and inductive logic to the research and data analysis.”

Researchers rely heavily on data as they have a story to tell or research problems to solve. It starts with a question, and data is nothing but an answer to that question. But, what if there is no question to ask? Well! It is possible to explore data even without a problem – we call it ‘Data Mining’, which often reveals some interesting patterns within the data that are worth exploring.

Irrelevant to the type of data researchers explore, their mission and audiences’ vision guide them to find the patterns to shape the story they want to tell. One of the essential things expected from researchers while analyzing data is to stay open and remain unbiased toward unexpected patterns, expressions, and results. Remember, sometimes, data analysis tells the most unforeseen yet exciting stories that were not expected when initiating data analysis. Therefore, rely on the data you have at hand and enjoy the journey of exploratory research.

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Every kind of data has a rare quality of describing things after assigning a specific value to it. For analysis, you need to organize these values, processed and presented in a given context, to make it useful. Data can be in different forms; here are the primary data types.

Qualitative data: When the data presented has words and descriptions, then we call it qualitative data . Although you can observe this data, it is subjective and harder to analyze data in research, especially for comparison. Example: Quality data represents everything describing taste, experience, texture, or an opinion that is considered quality data. This type of data is usually collected through focus groups, personal qualitative interviews , qualitative observation or using open-ended questions in surveys.
Quantitative data: Any data expressed in numbers of numerical figures are called quantitative data . This type of data can be distinguished into categories, grouped, measured, calculated, or ranked. Example: questions such as age, rank, cost, length, weight, scores, etc. everything comes under this type of data. You can present such data in graphical format, charts, or apply statistical analysis methods to this data. The (Outcomes Measurement Systems) OMS questionnaires in surveys are a significant source of collecting numeric data.
Categorical data: It is data presented in groups. However, an item included in the categorical data cannot belong to more than one group. Example: A person responding to a survey by telling his living style, marital status, smoking habit, or drinking habit comes under the categorical data. A chi-square test is a standard method used to analyze this data.

Learn More : Examples of Qualitative Data in Education

Data analysis in qualitative research

Data analysis and qualitative data research work a little differently from the numerical data as the quality data is made up of words, descriptions, images, objects, and sometimes symbols. Getting insight from such complicated information is a complicated process. Hence it is typically used for exploratory research and data analysis .

Although there are several ways to find patterns in the textual information, a word-based method is the most relied and widely used global technique for research and data analysis. Notably, the data analysis process in qualitative research is manual. Here the researchers usually read the available data and find repetitive or commonly used words.

For example, while studying data collected from African countries to understand the most pressing issues people face, researchers might find “food” and “hunger” are the most commonly used words and will highlight them for further analysis.

LEARN ABOUT: Level of Analysis

The keyword context is another widely used word-based technique. In this method, the researcher tries to understand the concept by analyzing the context in which the participants use a particular keyword.

For example , researchers conducting research and data analysis for studying the concept of ‘diabetes’ amongst respondents might analyze the context of when and how the respondent has used or referred to the word ‘diabetes.’

The scrutiny-based technique is also one of the highly recommended text analysis methods used to identify a quality data pattern. Compare and contrast is the widely used method under this technique to differentiate how a specific text is similar or different from each other.

For example: To find out the “importance of resident doctor in a company,” the collected data is divided into people who think it is necessary to hire a resident doctor and those who think it is unnecessary. Compare and contrast is the best method that can be used to analyze the polls having single-answer questions types .

Metaphors can be used to reduce the data pile and find patterns in it so that it becomes easier to connect data with theory.

Variable Partitioning is another technique used to split variables so that researchers can find more coherent descriptions and explanations from the enormous data.

LEARN ABOUT: Qualitative Research Questions and Questionnaires

There are several techniques to analyze the data in qualitative research, but here are some commonly used methods,

Content Analysis: It is widely accepted and the most frequently employed technique for data analysis in research methodology. It can be used to analyze the documented information from text, images, and sometimes from the physical items. It depends on the research questions to predict when and where to use this method.
Narrative Analysis: This method is used to analyze content gathered from various sources such as personal interviews, field observation, and surveys . The majority of times, stories, or opinions shared by people are focused on finding answers to the research questions.
Discourse Analysis: Similar to narrative analysis, discourse analysis is used to analyze the interactions with people. Nevertheless, this particular method considers the social context under which or within which the communication between the researcher and respondent takes place. In addition to that, discourse analysis also focuses on the lifestyle and day-to-day environment while deriving any conclusion.
Grounded Theory: When you want to explain why a particular phenomenon happened, then using grounded theory for analyzing quality data is the best resort. Grounded theory is applied to study data about the host of similar cases occurring in different settings. When researchers are using this method, they might alter explanations or produce new ones until they arrive at some conclusion.

LEARN ABOUT: 12 Best Tools for Researchers

Data analysis in quantitative research

The first stage in research and data analysis is to make it for the analysis so that the nominal data can be converted into something meaningful. Data preparation consists of the below phases.

Phase I: Data Validation

Data validation is done to understand if the collected data sample is per the pre-set standards, or it is a biased data sample again divided into four different stages

Fraud: To ensure an actual human being records each response to the survey or the questionnaire
Screening: To make sure each participant or respondent is selected or chosen in compliance with the research criteria
Procedure: To ensure ethical standards were maintained while collecting the data sample
Completeness: To ensure that the respondent has answered all the questions in an online survey. Else, the interviewer had asked all the questions devised in the questionnaire.

Phase II: Data Editing

More often, an extensive research data sample comes loaded with errors. Respondents sometimes fill in some fields incorrectly or sometimes skip them accidentally. Data editing is a process wherein the researchers have to confirm that the provided data is free of such errors. They need to conduct necessary checks and outlier checks to edit the raw edit and make it ready for analysis.

Phase III: Data Coding

Out of all three, this is the most critical phase of data preparation associated with grouping and assigning values to the survey responses . If a survey is completed with a 1000 sample size, the researcher will create an age bracket to distinguish the respondents based on their age. Thus, it becomes easier to analyze small data buckets rather than deal with the massive data pile.

LEARN ABOUT: Steps in Qualitative Research

After the data is prepared for analysis, researchers are open to using different research and data analysis methods to derive meaningful insights. For sure, statistical analysis plans are the most favored to analyze numerical data. In statistical analysis, distinguishing between categorical data and numerical data is essential, as categorical data involves distinct categories or labels, while numerical data consists of measurable quantities. The method is again classified into two groups. First, ‘Descriptive Statistics’ used to describe data. Second, ‘Inferential statistics’ that helps in comparing the data .

Descriptive statistics

This method is used to describe the basic features of versatile types of data in research. It presents the data in such a meaningful way that pattern in the data starts making sense. Nevertheless, the descriptive analysis does not go beyond making conclusions. The conclusions are again based on the hypothesis researchers have formulated so far. Here are a few major types of descriptive analysis methods.

Measures of Frequency

Count, Percent, Frequency
It is used to denote home often a particular event occurs.
Researchers use it when they want to showcase how often a response is given.

Measures of Central Tendency

Mean, Median, Mode
The method is widely used to demonstrate distribution by various points.
Researchers use this method when they want to showcase the most commonly or averagely indicated response.

Measures of Dispersion or Variation

Range, Variance, Standard deviation
Here the field equals high/low points.
Variance standard deviation = difference between the observed score and mean
It is used to identify the spread of scores by stating intervals.
Researchers use this method to showcase data spread out. It helps them identify the depth until which the data is spread out that it directly affects the mean.

Measures of Position

Percentile ranks, Quartile ranks
It relies on standardized scores helping researchers to identify the relationship between different scores.
It is often used when researchers want to compare scores with the average count.

For quantitative research use of descriptive analysis often give absolute numbers, but the in-depth analysis is never sufficient to demonstrate the rationale behind those numbers. Nevertheless, it is necessary to think of the best method for research and data analysis suiting your survey questionnaire and what story researchers want to tell. For example, the mean is the best way to demonstrate the students’ average scores in schools. It is better to rely on the descriptive statistics when the researchers intend to keep the research or outcome limited to the provided sample without generalizing it. For example, when you want to compare average voting done in two different cities, differential statistics are enough.

Descriptive analysis is also called a ‘univariate analysis’ since it is commonly used to analyze a single variable.

Inferential statistics

Inferential statistics are used to make predictions about a larger population after research and data analysis of the representing population’s collected sample. For example, you can ask some odd 100 audiences at a movie theater if they like the movie they are watching. Researchers then use inferential statistics on the collected sample to reason that about 80-90% of people like the movie.

Here are two significant areas of inferential statistics.

Estimating parameters: It takes statistics from the sample research data and demonstrates something about the population parameter.
Hypothesis test: I t’s about sampling research data to answer the survey research questions. For example, researchers might be interested to understand if the new shade of lipstick recently launched is good or not, or if the multivitamin capsules help children to perform better at games.

These are sophisticated analysis methods used to showcase the relationship between different variables instead of describing a single variable. It is often used when researchers want something beyond absolute numbers to understand the relationship between variables.

Here are some of the commonly used methods for data analysis in research.

Correlation: When researchers are not conducting experimental research or quasi-experimental research wherein the researchers are interested to understand the relationship between two or more variables, they opt for correlational research methods.
Cross-tabulation: Also called contingency tables, cross-tabulation is used to analyze the relationship between multiple variables. Suppose provided data has age and gender categories presented in rows and columns. A two-dimensional cross-tabulation helps for seamless data analysis and research by showing the number of males and females in each age category.
Regression analysis: For understanding the strong relationship between two variables, researchers do not look beyond the primary and commonly used regression analysis method, which is also a type of predictive analysis used. In this method, you have an essential factor called the dependent variable. You also have multiple independent variables in regression analysis. You undertake efforts to find out the impact of independent variables on the dependent variable. The values of both independent and dependent variables are assumed as being ascertained in an error-free random manner.
Frequency tables: The statistical procedure is used for testing the degree to which two or more vary or differ in an experiment. A considerable degree of variation means research findings were significant. In many contexts, ANOVA testing and variance analysis are similar.
Analysis of variance: The statistical procedure is used for testing the degree to which two or more vary or differ in an experiment. A considerable degree of variation means research findings were significant. In many contexts, ANOVA testing and variance analysis are similar.
Researchers must have the necessary research skills to analyze and manipulation the data , Getting trained to demonstrate a high standard of research practice. Ideally, researchers must possess more than a basic understanding of the rationale of selecting one statistical method over the other to obtain better data insights.
Usually, research and data analytics projects differ by scientific discipline; therefore, getting statistical advice at the beginning of analysis helps design a survey questionnaire, select data collection methods , and choose samples.

LEARN ABOUT: Best Data Collection Tools

The primary aim of data research and analysis is to derive ultimate insights that are unbiased. Any mistake in or keeping a biased mind to collect data, selecting an analysis method, or choosing audience sample il to draw a biased inference.
Irrelevant to the sophistication used in research data and analysis is enough to rectify the poorly defined objective outcome measurements. It does not matter if the design is at fault or intentions are not clear, but lack of clarity might mislead readers, so avoid the practice.
The motive behind data analysis in research is to present accurate and reliable data. As far as possible, avoid statistical errors, and find a way to deal with everyday challenges like outliers, missing data, data altering, data mining , or developing graphical representation.

LEARN MORE: Descriptive Research vs Correlational Research The sheer amount of data generated daily is frightening. Especially when data analysis has taken center stage. in 2018. In last year, the total data supply amounted to 2.8 trillion gigabytes. Hence, it is clear that the enterprises willing to survive in the hypercompetitive world must possess an excellent capability to analyze complex research data, derive actionable insights, and adapt to the new market needs.

LEARN ABOUT: Average Order Value

QuestionPro is an online survey platform that empowers organizations in data analysis and research and provides them a medium to collect data by creating appealing surveys.

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How to Create a Data Analysis Plan: A Detailed Guide

by Barche Blaise | Aug 12, 2020 | Writing

If a good research question equates to a story then, a roadmap will be very vita l for good storytelling. We advise every student/researcher to personally write his/her data analysis plan before seeking any advice. In this blog article, we will explore how to create a data analysis plan: the content and structure.

This data analysis plan serves as a roadmap to how data collected will be organised and analysed. It includes the following aspects:

Clearly states the research objectives and hypothesis
Identifies the dataset to be used
Inclusion and exclusion criteria
Clearly states the research variables
States statistical test hypotheses and the software for statistical analysis
Creating shell tables

1. Stating research question(s), objectives and hypotheses:

All research objectives or goals must be clearly stated. They must be Specific, Measurable, Attainable, Realistic and Time-bound (SMART). Hypotheses are theories obtained from personal experience or previous literature and they lay a foundation for the statistical methods that will be applied to extrapolate results to the entire population.

2. The dataset:

The dataset that will be used for statistical analysis must be described and important aspects of the dataset outlined. These include; owner of the dataset, how to get access to the dataset, how the dataset was checked for quality control and in what program is the dataset stored (Excel, Epi Info, SQL, Microsoft access etc.).

3. The inclusion and exclusion criteria :

They guide the aspects of the dataset that will be used for data analysis. These criteria will also guide the choice of variables included in the main analysis.

4. Variables:

Every variable collected in the study should be clearly stated. They should be presented based on the level of measurement (ordinal/nominal or ratio/interval levels), or the role the variable plays in the study (independent/predictors or dependent/outcome variables). The variable types should also be outlined. The variable type in conjunction with the research hypothesis forms the basis for selecting the appropriate statistical tests for inferential statistics. A good data analysis plan should summarize the variables as demonstrated in Figure 1 below.

Presentation of variables in a data analysis plan

5. Statistical software

There are tons of software packages for data analysis, some common examples are SPSS, Epi Info, SAS, STATA, Microsoft Excel. Include the version number, year of release and author/manufacturer. Beginners have the tendency to try different software and finally not master any. It is rather good to select one and master it because almost all statistical software have the same performance for basic and the majority of advance analysis needed for a student thesis. This is what we recommend to all our students at CRENC before they begin writing their results section .

6. Selecting the appropriate statistical method to test hypotheses

Depending on the research question, hypothesis and type of variable, several statistical methods can be used to answer the research question appropriately. This aspect of the data analysis plan outlines clearly why each statistical method will be used to test hypotheses. The level of statistical significance (p-value) which is often but not always <0.05 should also be written. Presented in figures 2a and 2b are decision trees for some common statistical tests based on the variable type and research question

A good analysis plan should clearly describe how missing data will be analysed.

How to choose a statistical method to determine association between variables

7. Creating shell tables

Data analysis involves three levels of analysis; univariable, bivariable and multivariable analysis with increasing order of complexity. Shell tables should be created in anticipation for the results that will be obtained from these different levels of analysis. Read our blog article on how to present tables and figures for more details. Suppose you carry out a study to investigate the prevalence and associated factors of a certain disease “X” in a population, then the shell tables can be represented as in Tables 1, Table 2 and Table 3 below.

Table 1: Example of a shell table from univariate analysis

Table 2: Example of a shell table from bivariate analysis

Table 3: Example of a shell table from multivariate analysis

aOR = adjusted odds ratio

Now that you have learned how to create a data analysis plan, these are the takeaway points. It should clearly state the:

Research question, objectives, and hypotheses
Dataset to be used
Variable types and their role
Statistical software and statistical methods
Shell tables for univariate, bivariate and multivariate analysis

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Home » How To Write A Research Proposal – Step-by-Step [Template]

How To Write A Research Proposal – Step-by-Step [Template]

Table of Contents

How To Write a Research Proposal

Writing a Research proposal involves several steps to ensure a well-structured and comprehensive document. Here is an explanation of each step:

1. Title and Abstract

Choose a concise and descriptive title that reflects the essence of your research.
Write an abstract summarizing your research question, objectives, methodology, and expected outcomes. It should provide a brief overview of your proposal.

2. Introduction:

Provide an introduction to your research topic, highlighting its significance and relevance.
Clearly state the research problem or question you aim to address.
Discuss the background and context of the study, including previous research in the field.

3. Research Objectives

Outline the specific objectives or aims of your research. These objectives should be clear, achievable, and aligned with the research problem.

4. Literature Review:

Conduct a comprehensive review of relevant literature and studies related to your research topic.
Summarize key findings, identify gaps, and highlight how your research will contribute to the existing knowledge.

5. Methodology:

Describe the research design and methodology you plan to employ to address your research objectives.
Explain the data collection methods, instruments, and analysis techniques you will use.
Justify why the chosen methods are appropriate and suitable for your research.

6. Timeline:

Create a timeline or schedule that outlines the major milestones and activities of your research project.
Break down the research process into smaller tasks and estimate the time required for each task.

7. Resources:

Identify the resources needed for your research, such as access to specific databases, equipment, or funding.
Explain how you will acquire or utilize these resources to carry out your research effectively.

8. Ethical Considerations:

Discuss any ethical issues that may arise during your research and explain how you plan to address them.
If your research involves human subjects, explain how you will ensure their informed consent and privacy.

9. Expected Outcomes and Significance:

Clearly state the expected outcomes or results of your research.
Highlight the potential impact and significance of your research in advancing knowledge or addressing practical issues.

10. References:

Provide a list of all the references cited in your proposal, following a consistent citation style (e.g., APA, MLA).

11. Appendices:

Include any additional supporting materials, such as survey questionnaires, interview guides, or data analysis plans.

Research Proposal Format

The format of a research proposal may vary depending on the specific requirements of the institution or funding agency. However, the following is a commonly used format for a research proposal:

1. Title Page:

Include the title of your research proposal, your name, your affiliation or institution, and the date.

2. Abstract:

Provide a brief summary of your research proposal, highlighting the research problem, objectives, methodology, and expected outcomes.

3. Introduction:

Introduce the research topic and provide background information.
State the research problem or question you aim to address.
Explain the significance and relevance of the research.
Review relevant literature and studies related to your research topic.
Summarize key findings and identify gaps in the existing knowledge.
Explain how your research will contribute to filling those gaps.

5. Research Objectives:

Clearly state the specific objectives or aims of your research.
Ensure that the objectives are clear, focused, and aligned with the research problem.

6. Methodology:

Describe the research design and methodology you plan to use.
Explain the data collection methods, instruments, and analysis techniques.
Justify why the chosen methods are appropriate for your research.

7. Timeline:

8. Resources:

Explain how you will acquire or utilize these resources effectively.

9. Ethical Considerations:

If applicable, explain how you will ensure informed consent and protect the privacy of research participants.

10. Expected Outcomes and Significance:

11. References:

12. Appendices:

Research Proposal Template

Here’s a template for a research proposal:

1. Introduction:

2. Literature Review:

3. Research Objectives:

4. Methodology:

5. Timeline:

6. Resources:

7. Ethical Considerations:

8. Expected Outcomes and Significance:

9. References:

10. Appendices:

Research Proposal Sample

Title: The Impact of Online Education on Student Learning Outcomes: A Comparative Study

1. Introduction

Online education has gained significant prominence in recent years, especially due to the COVID-19 pandemic. This research proposal aims to investigate the impact of online education on student learning outcomes by comparing them with traditional face-to-face instruction. The study will explore various aspects of online education, such as instructional methods, student engagement, and academic performance, to provide insights into the effectiveness of online learning.

2. Objectives

The main objectives of this research are as follows:

To compare student learning outcomes between online and traditional face-to-face education.
To examine the factors influencing student engagement in online learning environments.
To assess the effectiveness of different instructional methods employed in online education.
To identify challenges and opportunities associated with online education and suggest recommendations for improvement.

3. Methodology

3.1 Study Design

This research will utilize a mixed-methods approach to gather both quantitative and qualitative data. The study will include the following components:

3.2 Participants

The research will involve undergraduate students from two universities, one offering online education and the other providing face-to-face instruction. A total of 500 students (250 from each university) will be selected randomly to participate in the study.

3.3 Data Collection

The research will employ the following data collection methods:

Quantitative: Pre- and post-assessments will be conducted to measure students’ learning outcomes. Data on student demographics and academic performance will also be collected from university records.
Qualitative: Focus group discussions and individual interviews will be conducted with students to gather their perceptions and experiences regarding online education.

3.4 Data Analysis

Quantitative data will be analyzed using statistical software, employing descriptive statistics, t-tests, and regression analysis. Qualitative data will be transcribed, coded, and analyzed thematically to identify recurring patterns and themes.

4. Ethical Considerations

The study will adhere to ethical guidelines, ensuring the privacy and confidentiality of participants. Informed consent will be obtained, and participants will have the right to withdraw from the study at any time.

5. Significance and Expected Outcomes

This research will contribute to the existing literature by providing empirical evidence on the impact of online education on student learning outcomes. The findings will help educational institutions and policymakers make informed decisions about incorporating online learning methods and improving the quality of online education. Moreover, the study will identify potential challenges and opportunities related to online education and offer recommendations for enhancing student engagement and overall learning outcomes.

6. Timeline

The proposed research will be conducted over a period of 12 months, including data collection, analysis, and report writing.

The estimated budget for this research includes expenses related to data collection, software licenses, participant compensation, and research assistance. A detailed budget breakdown will be provided in the final research plan.

8. Conclusion

This research proposal aims to investigate the impact of online education on student learning outcomes through a comparative study with traditional face-to-face instruction. By exploring various dimensions of online education, this research will provide valuable insights into the effectiveness and challenges associated with online learning. The findings will contribute to the ongoing discourse on educational practices and help shape future strategies for maximizing student learning outcomes in online education settings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research Methods and Design

Module 6: data sources and proposal, how to write a research proposal.

At the end of this subject, the main product you should have to show for it is a research proposal. A research proposal helps your colleagues and supervisors evaluate you proposed research, assess the appropriateness of you methods, and identify problems ahead of time, sot hey can be fixed.

This pathway will provide you with the understanding needed for writing up your research proposal. It will explain the components of a research proposal, and provide you with a template for writing it up.

Understand the components of a research proposal
Understand the process of writing up a research proposal
Become familiar with the format and template of a UOW research proposal

Research proposal template

At the university of Wollongong, in the Faculty of Law, Humanities and the Arts, there are some expectations with regards to research proposals. Prospective Honours/Masters by Research/PhD students are required to complete a research proposal and submit this with the formal application form and relevant documents. The proposal should be no more than 3,000 words in length (excluding references). The numbers in parentheses indicate an estimate of the portion that should be devoted to each section. This does not suggest that all sections should be this portion exactly, but it should provide guidance as to the relative priorities of the proposal. The proposal should contain the following elements.

Suggested research title
Introduction (15%) – The introduction should situate the question(s) you are addressing. Why is the question important? How will answering it advance knowledge in international studies? What is the broader social/political/geopolitical context that frames your question? What are the broader issues that the research is trying to explain? (Be sure your research question(s) are clearly stated in this section)
Literature review (25%) – The literature review should demonstrate that your research question is anchored in and contributes to a body of literature(s). You should demonstrate awareness of key research in the relevant fields and provide an analytical summary of current knowledge. This section should also describe and justify the general theoretical approach/framework applied in your proposed research.
Research design (10%) – This section should describe your approach to researching the proposed problem. The research design (descriptive, comparative, case study, narrative, etc.) should be described and justified as appropriate to address the research problem you have identified.
Methods and Data (20%) – This section should indicate the data sources needed to answer the research question and the general methodological approach taken. Items to address include: key propositions or hypotheses; concepts; independent and dependent variable(s); indicators; cross-section or longitudinal approach; unit of analysis; sampling; validity and reliability; etc. (Please note: not all of these topics apply for all projects so please address what is relevant to your work.) For students doing theory based projects please indicate what data sources you will utilise and your general method.
Proposed analyses (20%) – This section should describe how you intend to analyse the data to address your research question(s). Is the project qualitative, quantitative or a mixed methods approach? Please identify the techniques you will use to analyse the data. Note: qualitative methods typically require coding AND analysis of data. Both stages should be described in this section
Proposed timeframe for the study (10%) – Outline a timetable for completion of the project (6 months for honours, 2 years for full-time Masters students, 3 years for PhD).

Components of a research proposal

A research proposal begins with a title page. The title is centered in the upper half of the page, with each important word capitalized. The title should clearly and concisely (in about 12 words or fewer) communicate the primary variables and research questions. This sometimes requires a main title followed by a subtitle that elaborates on the main title, in which case the main title and subtitle are separated by a colon. Here are some titles from recent issues of professional international studies journals:

Benefits of global partnerships to facilitate access to medicines in developing countries: a multi-country analysis of patients and patient outcomes in GIPAP
Grounding the European public sphere: looking beyond the mass media to digitally mediated issue publics
“Smartness” without vision: the Moroccan regime in the face of acquiescent elites and weak social mobilization

Introduction

The introduction begins on the second page of the proposal. The heading at the top of this page is the full title of the manuscript, with each important word capitalized as on the title page. The introduction usually includes three distinct subsections, although these are typically not identified by separate headings. The opening introduces the research question and explains why it is interesting, the literature review discusses relevant previous research, and the closing restates the research question and comments on the method used to answer it.

Tip: write the introduction last. It makes sense to start writing the introduction first, but in fact, after your proposal is written, you will often find that the introduction is easier to write. You will then have a better understanding of what background is relevant to the reader, and what needs to be emphasised.

The opening , which is usually a paragraph or two in length, introduces the research question and explains what is interesting about it, and who it is interesting/important to. To capture the reader’s attention, researcher Daryl Bem [1] recommends starting with general observations about the topic under study, expressed in ordinary language (not technical jargon)—observations that are about people and their behaviour (not about researchers or their research). After capturing the reader’s attention, the opening should go on to introduce the research question and explain why it is interesting. Will the answer fill a gap in the literature? Will it provide a test of an important theory? Does it have practical implications? Giving readers a clear sense of what the research is about and why they should care about it will motivate them to continue reading the literature review—and will help them make sense of it.

A condensed literature review : Immediately after the opening comes a condensed literature review, which describes relevant previous research on the topic in a condensed way. It should NOT be simply a list of past studies. Instead, it constitutes a kind of argument for why the research question is worth addressing. By the end of the literature review, readers should be convinced that the research question makes sense and that the present study is a logical next step in the ongoing research process. It is not your full literature review at this stage, but just a sample of the main tenants of your argument, which lead to the way you plan to address your research questions. The closing of the introduction — typically the final paragraph or two — usually includes two important elements. The first is a clear statement of the main research question or hypothesis. This statement tends to be more formal and precise than in the opening and is often expressed in terms of operational definitions of the key variables. The second is a brief overview of the method and some comment on its appropriateness.

Literature review

The purpose of the literature review is to develop an argument for the method you chose to use in our research, and why this method is suitable for addressing your research question. The argument has to be based on scholarly academic sources. The literature review is also meant to give the reader a summary of the current knowledge on your topic: how can you group the various authors under consideration? What assumptions do they share? Do they agree about the implications of their work? Do they prioritize things the same and/or correctly? what gaps are there in those views? Like any effective argument, the literature review must have some kind of structure. For example, it might begin by describing a phenomenon in a general way along with several studies that demonstrate it, then describing two or more competing theories of the phenomenon, and finally presenting a hypothesis to test one or more of the theories. Or it might describe one phenomenon, then describe another phenomenon that seems inconsistent with the first one, then propose a theory that resolves the inconsistency, and finally present a hypothesis to test that theory. In applied research, it might describe a phenomenon or theory, then describe how that phenomenon or theory applies to some important real-world situation, and finally suggest a way to test whether it does, in fact, apply to that situation. Looking at the literature review in this way emphasizes a few things:

It is extremely important to start with an outline of the main points that you want to make, organised in the order that you want to make them. The basic structure of your argument, then, should be apparent from the outline itself.
It is important to emphasise the structure of your argument in your writing. One way to do this is to begin the literature review by summarising your argument even before you begin to make it. “This proposal describes two apparently contradictory phenomena, present a new theory that has the potential to resolve the apparent contradiction, and finally present a novel hypothesis to test the theory.” Another way is to open each paragraph with a sentence that summarises the main point of the paragraph and links it to the preceding points. These opening sentences provide the “transitions” that many beginning researchers have difficulty with. Instead of beginning a paragraph by jumping into a description of a previous study, such as “Williams (2004) found that…,” it is better to start by indicating something about why you are describing this particular study. Here are some simple examples:

Another example of this phenomenon comes from the work of Williams (2004). Williams (2004) offers one explanation of this phenomenon. An alternative perspective has been provided by Williams (2004). We used a method based on the one used by Williams (2004).

Remember that your goal is to construct an argument for why your research question is interesting and worth addressing—not necessarily why your favourite answer to it is correct. In other words, your literature review must be balanced. If you want to emphasise the generality of a phenomenon, then of course you should discuss various studies that have demonstrated it. However, if there are other studies that have failed to demonstrate it, you should discuss them too. Or if you are proposing a new theory, then of course you should discuss findings that are consistent with that theory. However, if there are other findings that are inconsistent with it, again, you should discuss them too. It is acceptable to argue that the balance of the research supports the existence of a phenomenon or is consistent with a theory (and that is usually the best that researchers in psychology can hope for), but it is not acceptable to ignore contradictory evidence. Besides, a large part of what makes a research question interesting is uncertainty about its answer.

Research design

In this section, you need to not only describe your research design, but also explain how that design is beneficial for answering your research questions. Does it provide breadth? depth? objectivity? The research design can usually be justified with previous research which has used a similar design, or, in contrast, by showing that there is little research in the area using such design, and a need for it.

Methods and data

The methods and data section is where you describe how you conducted your data collection. An important principle for writing a method section is that it should be clear and detailed enough that other researchers could replicate the study by following your “recipe.” This means that it must describe all the important elements of the study—basic demographic characteristics of the participants, how they were recruited, whether they were randomly assigned, how the variables were manipulated or measured, how counterbalancing was accomplished, and so on. At the same time, it should avoid irrelevant details such as the fact that the study was conducted in Classroom 37B of the Industrial Technology Building or that the questionnaire was double-sided and completed using pencils. The method section begins immediately after the introduction ends with the heading “Methods”. Immediately after this is the subheading “Participants,” which indicates how many participants you intend to involve (if any), and how they will be recruited.

Reflection activity: research proposal

Share the answers to the following questions with the group in the discussion forum.

What aspect of the research proposal task do you currently find the most challenging and why?
↑ Bem, D. J. (2003). Writing the empirical journal article. In J. M. Darley, M. P. Zanna, & H. R. Roediger III (Eds.), The compleat academic: A practical guide for the beginning social scientist (2nd ed.). Washington, DC: American Psychological Association.

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Top 10 Data Analysis Research Proposal Templates with Examples and Samples

Himani Khatri

In a world awash with data, the real challenge lies not in the abundance of information but in deciphering its true meaning, making sense of the chaos, and addressing pressing real-world problems. If you're a researcher or student, you know the struggle: the pain points of grappling with data quality, precision, and relevance. It's these very challenges that underscore the critical importance of crafting a well-structured data analysis research proposal.

Think of it as your toolkit, a roadmap to navigate the complexities of data-driven research and turn information into solutions. In this blog, we're here to help you master the art of creating a data analysis research proposal, providing you with the key to unlock the answers to those nagging questions, and offer solutions (Our editable templates) to problems that keep you up at night.

As we start this journey, let's draw inspiration from two illustrious examples, Google Flu Trends and Netflix's Recommendation Algorithm, which have not only captured the limelight but have tackled data-related pain points and transformed them into remarkable solutions. These examples will serve as guiding stars as we navigate the intricacies of data analysis to craft proposals that address real-world issues head-on.

Google Flu Trends : Conquering the Challenge of Data Accuracy

Imagine having the power to predict flu outbreaks with uncanny precision. Google Flu Trends did just that, tapping into the vast sea of search queries. But it wasn't just about innovation; it was also about recognizing the persistent pain point of data accuracy and modeling. The project revealed that behind every data analysis success story lies the challenge of ensuring data quality and building models that stand up to the rigorous demands of real-world problems.

Netflix's Recommendation Algorithm : Navigating the Data Overload Dilemma

In the world of entertainment, where options seem endless, Netflix's Recommendation Algorithm emerged as a winner. It tackled the overwhelming pain point of information overload by leveraging data to understand users better. The result? A recommendation system that not only improved user satisfaction but also demonstrated how data analysis can help individuals navigate through the ever-growing sea of choices and make their lives easier.

In these two case studies, we uncover the real-world challenges that data analysis can address, from accuracy dilemmas to information overload.

Let's explore the research proposal presentation templates now!

Template 1: Data Analysis in Research Proposal

Click Here to Download

Introducing this cover slide of the proposal that has been professionally designed and sets the stage for your entire research proposal. With ample space for an image, it captures your audience's attention from the start. Your proposal's credentials, both for the recipient and the preparer, can be displayed. Both researchers and professionals can take assistance to streamline the presentation creation process, leaving you more time to focus on your data analysis. Make a lasting impression and get your proposal noticed with this polished, easy-to-use template.

Template 2: Cover Letter for Research Data Analysis Proposal

Introducing this Cover Letter Slide, which will help you make a lasting impression in the world of research and analytics. We understand the importance of clear and concise communication in proposals. Our professionally crafted slide provides a perfect introduction, addressing your customers and outlining your company's objectives. Say goodbye to the hassle of creating proposals from scratch – with our ready-made slide, you can simply insert your details and be on your way to success. This cover letter helps you state that your experience and expertise will help your audience achieve their goals effortlessly. Don't miss this opportunity – grab this proposal slide and make a strong, confident start in the world of data analytics.

Template 3 – Project Context and Objectives of Research Data Analysis Proposal

This slide simplifies the process of impressing your clients. It explains your project's context and objectives, leaving a lasting impact on your audience.

Project Context: We provide a clear and concise space for explaining the background and significance of your research, setting the stage for your proposal.

Project Objectives: Clearly outline your research goals and what you aim to achieve, ensuring everyone understands your mission.

Make your research proposal shine with this template at your disposal.

Template 4: Scope of Work for Research Data Analysis Proposal

This slide outlines your research data analysis journey, making client presentations a breeze. Our scope of work slide covers all the essentials: Acquisition & Extraction, Examination, Cleaning, Transformation, Exploration, and Analysis, leading to the grand finale - Presenting and Sharing your findings. With clear and easy-to-understand visuals, impress your clients and streamline your workflow.

Template 5: Plan of Action for Research Data Analysis Proposal

Are you looking to present your research data analysis plan with clarity and professionalism? Our ready-made PowerPoint slide has got you covered. This user-friendly template features a visual diagram illustrating the entire process, from data collection through pre-processing, analysis, and classification. With easy-to-understand icons and clear labels, you can effectively convey your plan to your audience.

Template 6: Timeline for Research Data Analysis Project

Designed with simplicity, this timeline slide offers a user-friendly layout to help you convey complex ideas easily. It covers every crucial step of your analysis journey, from tackling business issues to final presentation. With vibrant visuals and customizable elements, you can effortlessly illustrate data understanding, preparation, exploratory analysis, validation, and visualization. Get it today!

Template 7: Key Deliverables for Research Data Analysis Proposal

With clear, concise visuals, this slide presents your key deliverables. From ‘Decision Mapping’ that outlines your project's path to ‘Analysis and Design’ for robust strategies, and ‘Implementation’ for real-world action, it's all here. Even better, it highlights ‘Ongoing Steps’ for sustained success. Why waste time on complex slides when you can have this ready-made gem? Elevate your presentations and win your audience over with this template at your disposal.

Template 8: Why Our Data Analytics Company?

This slide helps you showcase why people should choose your company rather than your competitors. Elucidate what makes your organization stand out from the rest by taking assistance of this readily-available PowerPoint slide.

It lists down the strength that keeps your firm on the top in comparison with your rivals.

Some of the strengths mentioned in the slide are:

Reduced churn rate
Reduced operational cost
Increased revenue
Faster data analysis reporting

Template 9: Services Offered by Data Analytics Company

This slide presents the services offered by data analysis company in a clear and precise way. Get your hands on this slide to present your offerings. The template encapsulates services like data collection services, data quality assess, data integration, policy analytics, social media and digital outreach, enterprise analytics, and more.

Template 10: Team Structure of Data Analysis Company

The slide presents team structure of data analytics company in a comprehensive format. A hierarchy chart makes it easy for organization to showcase their talented staff and the driving forces behind their firm’s success, this is where this template comes into assistance. Put your hands on this template to present head of advanced analytics, COE Support office, demand management, analytics development, analytics support, etc.

Team Structure of Data Analysis Company 1/2

These templates are your one-stop solution for crafting compelling Research Data Analysis Proposals.

With a subscription to our service, you gain access to an extensive library of ready-made PowerPoint templates that will save you time and effort. But that's not all – if you require a personalized touch, our team can also design a custom proposal that perfectly aligns with your unique needs.

Why wait? Join our community of satisfied customers and supercharge your research endeavors today.

Subscribe now and get your hands on impactful presentations!

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Helpful Tips on Composing a Research Paper Data Analysis Section

If you are given a research paper assignment, you should create a list of tasks to be done and try to stick to your working schedule. It is recommended that you complete your research and then start writing your work. One of the important steps is to prepare your data analysis section. However, that step is vital as it aims to explain how the data will be described in the results section. Use the following helpful tips to complete that section without a hitch.

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How to Compose a Data Analysis Section for Your Research Paper

Usually, a data analysis section is provided right after the methods and approaches used. There, you should explain how you organized your data, what statistical tests were applied, and how you evaluated the obtained results. Follow these simple tips to compose a strong piece of writing:

Avoid analyzing your results in the data analysis section.
Indicate whether your research is quantitative or qualitative.
Provide your main research questions and the analysis methods that were applied to answer them.
Report what software you used to gather and analyze your data.
List the data sources, including electronic archives and online reports of different institutions.
Explain how the data were summarized and what measures of variability you have used.
Remember to mention the data transformations if any, including data normalizing.
Make sure that you included the full name of statistical tests used.
Describe graphical techniques used to analyze the raw data and the results.

Where to Find the Necessary Assistance If You Get Stuck

Research paper writing is hard, so if you get stuck, do not wait for enlightenment and start searching for some assistance. It is a good idea to consult a statistics expert if you have a large amount of data and have no idea on how to summarize it. Your academic advisor may suggest you where to find a statistician to ask your questions.

Another great help option is getting a sample of a data analysis section. At the school’s library, you can find sample research papers written by your fellow students, get a few works, and study how the students analyzed data. Pay special attention to the word choices and the structure of the writing.

If you decide to follow a section template, you should be careful and keep your professor’s instructions in mind. For example, you may be asked to place all the page-long data tables in the appendices or build graphs instead of providing tables.

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COMMENTS

Creating a Data Analysis Plan: What to Consider When Choosing
For those interested in conducting qualitative research, previous articles in this Research Primer series have provided information on the design and analysis of such studies. 2, 3 Information in the current article is divided into 3 main sections: an overview of terms and concepts used in data analysis, a review of common methods used to ...
How to Write a Research Proposal
A research proposal describes what you will investigate, ... your research design or methodology section will describe your overall approach, and the practical steps you will take to answer your research questions. Building a research proposal methodology; ... Finalize sampling methods and data analysis methods; 13th February: 3. Data ...
Data Analysis in Quantitative Research Proposal
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In the methods section of an APA research paper, you report in detail the participants, measures, and procedure of your study. ... the research design and data analysis strategy, including any steps taken to transform the data and statistical analyses. ... The same basic structure also applies to a thesis, dissertation, or research proposal.
PDF Developing a Quantitative Data Analysis Plan
A Data Analysis Plan (DAP) is about putting thoughts into a plan of action. Research questions are often framed broadly and need to be clarified and funnelled down into testable hypotheses and action steps. The DAP provides an opportunity for input from collaborators and provides a platform for training. Having a clear plan of action is also ...
Data Analytics Resources: Writing a Research Proposal
A research proposal describes what you will investigate, why it's important, and how you will conduct your research. Your paper should include the topic, research question and hypothesis, methods, predictions, and results (if not actual, then projected). ... Demonstrate that you have carefully considered the data, tools, and procedures ...
PDF DATA ANALYSIS PLAN
•Data are random numbers. Plan accordingly. • Statistical analysis is the language of scientific inference. Expand your vocabulary. • Statistical analysis is harder than it looks. • Get help now, before you start writing. • Get help while you are writing. • Budget help for later. • When in doubt, call statistician. • When not in doubt, call statistician.
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This article is a practical guide to conducting data analysis in general literature reviews. The general literature review is a synthesis and analysis of published research on a relevant clinical issue, and is a common format for academic theses at the bachelor's and master's levels in nursing, physiotherapy, occupational therapy, public health and other related fields.
Writing a Research Proposal
Writing a Case Analysis Paper; Writing a Case Study; Writing a Field Report Toggle Dropdown. ... and consider the use of different methods for gathering and analyzing data related to the research problem; and, ... In a standard research proposal, this section can take two forms, so consult with your professor about which one is preferred. ...
How to write a research proposal?
The objective of preparing a research proposal would be to obtain approvals from various committees including ethics committee [details under 'Research methodology II' section ... Data analysis . This section deals with the reduction and reconstruction of data and its analysis including sample size calculation. The researcher is expected to ...
PDF Chapter 22 Writing the Data Analysis Plan
sections of your grant proposal. ... selected quantitative models once the data are collected. The data analysis section is critical for you - not simply because you want your reviewers to understand that ... How to Write a Successful Research Grant Application: A Guide for Social and Behavioral Scientists, DOI 10.1007/978-1-4419-1454-5_22,
Designing Research Proposal in Quantitative Approach
The rationale section of a research proposal is often incorporated in the introduction part. Wherever it is placed, either in the introduction or separately, the main thrust of this section is to prove that the proposed research is new and worthwhile. ... Data processing and analysis: Data will be computerized, analysed, and interpreted using ...
Writing the Data Analysis Plan
Proposal lengths vary, but proportionally your data analysis section should not be a short section of your proposal. Unless you have a simple design that involves very few analyses (e.g., a 2 × 2 analysis of variance), you should plan to allocate at least 10-20% of your proposal to this section.
Data Analysis in Research: Types & Methods
Definition of research in data analysis: According to LeCompte and Schensul, research data analysis is a process used by researchers to reduce data to a story and interpret it to derive insights. The data analysis process helps reduce a large chunk of data into smaller fragments, which makes sense. Three essential things occur during the data ...
How to Create a Data Analysis Plan: A Detailed Guide
In this blog article, we will explore how to create a data analysis plan: the content and structure. This data analysis plan serves as a roadmap to how data collected will be organised and analysed. It includes the following aspects: Clearly states the research objectives and hypothesis. Identifies the dataset to be used.
How to write statistical analysis section in medical research
Abstract. Reporting of statistical analysis is essential in any clinical and translational research study. However, medical research studies sometimes report statistical analysis that is either inappropriate or insufficient to attest to the accuracy and validity of findings and conclusions. Published works involving inaccurate statistical ...
How To Write A Research Proposal
Include any additional supporting materials, such as survey questionnaires, interview guides, or data analysis plans. Research Proposal Format. The format of a research proposal may vary depending on the specific requirements of the institution or funding agency. However, the following is a commonly used format for a research proposal: 1. Title ...
PDF How to Write the Methods Section of a Research Paper
The methods section should describe what was done to answer the research question, describe how it was done, justify the experimental design, and explain how the results were analyzed. Scientific writing is direct and orderly. Therefore, the methods section structure should: describe the materials used in the study, explain how the materials ...
PDF WRITING AN EFFECTIVE RESEARCH PROPOSAL
research proposal is the formal description of this process. The first part of the proposal will include the research question to be answered along with a statement of why the area of research is important and what is known already. The second part of the proposal is the methods section, where the plan for answering the research question is given.
How to write a research proposal
Methods and Data (20%) - This section should indicate the data sources needed to answer the research question and the general methodological approach taken. Items to address include: key propositions or hypotheses; concepts; independent and dependent variable(s); indicators; cross-section or longitudinal approach; unit of analysis; sampling ...
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Data Analysis Plan Templates
Statistics Solutions provides a data analysis plan template based on your selected analysis. These templates are available from within Intellectus Statistics (see video). You can use these templates to develop the data analysis section of your dissertation or research proposal. If you do not know your analysis, you can figure it out using the ...
How To Write The Research Paper Data Analysis Section
Follow these simple tips to compose a strong piece of writing: Avoid analyzing your results in the data analysis section. Indicate whether your research is quantitative or qualitative. Provide your main research questions and the analysis methods that were applied to answer them. Report what software you used to gather and analyze your data.