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So now that you’ve completed the research project, what do you do? I know you won’t want to hear this, but your work is still far from done. In fact, this final stage – writing up your research – may be one of the most difficult. Developing a good, effective and concise report is an art form in itself. And, in many research projects you will need to write multiple reports that present the results at different levels of detail for different audiences.

There are several general considerations to keep in mind when generating a report:

Formatting Considerations

Are you writing a research report that you will submit for publication in a journal? If so, you should be aware that every journal requires articles that you follow specific formatting guidelines. Thinking of writing a book. Again, every publisher will require specific formatting. Writing a term paper? Most faculty will require that you follow specific guidelines. Doing your thesis or dissertation? Every university I know of has very strict policies about formatting and style. There are legendary stories that circulate among graduate students about the dissertation that was rejected because the page margins were a quarter inch off or the figures weren’t labeled correctly.

To illustrate what a set of research report specifications might include, I present in this section general guidelines for the formatting of a research write-up for a class term paper. These guidelines are very similar to the types of specifications you might be required to follow for a journal article. However, you need to check the specific formatting guidelines for the report you are writing – the ones presented here are likely to differ in some ways from any other guidelines that may be required in other contexts.

I’ve also included a sample research paper write-up that illustrates these guidelines. This sample paper is for a “make-believe” research project. But it illustrates how a final research report might look using the guidelines given here.

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• Methodology

Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism, run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation 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, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

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

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Cite this Scribbr article

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McCombes, S. (2023, March 20). Research Design | Step-by-Step Guide with Examples. Scribbr. Retrieved 10 July 2024, from https://www.scribbr.co.uk/research-methods/research-design/

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Shona McCombes

Research Methodology Example

Detailed Walkthrough + Free Methodology Chapter Template

If you’re working on a dissertation or thesis and are looking for an example of a research methodology chapter , you’ve come to the right place.

In this video, we walk you through a research methodology from a dissertation that earned full distinction , step by step. We start off by discussing the core components of a research methodology by unpacking our free methodology chapter template . We then progress to the sample research methodology to show how these concepts are applied in an actual dissertation, thesis or research project.

If you’re currently working on your research methodology chapter, you may also find the following resources useful:

• Research methodology 101 : an introductory video discussing what a methodology is and the role it plays within a dissertation
• Research design 101 : an overview of the most common research designs for both qualitative and quantitative studies
• Variables 101 : an introductory video covering the different types of variables that exist within research.
• Sampling 101 : an overview of the main sampling methods
• Methodology tips : a video discussion covering various tips to help you write a high-quality methodology chapter
• Private coaching : Get hands-on help with your research methodology

PS – If you’re working on a dissertation, be sure to also check out our collection of dissertation and thesis examples here .

FAQ: Research Methodology Example

Research methodology example: frequently asked questions, is the sample research methodology real.

Yes. The chapter example is an extract from a Master’s-level dissertation for an MBA program. A few minor edits have been made to protect the privacy of the sponsoring organisation, but these have no material impact on the research methodology.

Can I replicate this methodology for my dissertation?

As we discuss in the video, every research methodology will be different, depending on the research aims, objectives and research questions. Therefore, you’ll need to tailor your literature review to suit your specific context.

You can learn more about the basics of writing a research methodology chapter here .

Where can I find more examples of research methodologies?

The best place to find more examples of methodology chapters would be within dissertation/thesis databases. These databases include dissertations, theses and research projects that have successfully passed the assessment criteria for the respective university, meaning that you have at least some sort of quality assurance.

The Open Access Thesis Database (OATD) is a good starting point.

How do I get the research methodology chapter template?

You can access our free methodology chapter template here .

Is the methodology template really free?

Yes. There is no cost for the template and you are free to use it as you wish.

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Qualitative Research Resources: Writing Up Your Research

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• What is Qualitative Research?
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About this Page

Writing conventions for qualitative research, sample size/sampling:.

• Integrating Qualitative Research into Systematic Reviews
• Publishing Qualitative Research
• Presenting Qualitative Research
• Qualitative & Libraries: a few gems
• Data Repositories

Why is this information important?

• The conventions of good writing and research reporting are different for qualitative and quantitative research.
• Your article will be more likely to be published if you make sure you follow appropriate conventions in your writing.

On this page you will find the following helpful resources:

• Articles with information on what journal editors look for in qualitative research articles.
• Articles and books on the craft of collating qualitative data into a research article.

These articles provide tips on what journal editors look for when they read qualitative research papers for potential publication.  Also see Assessing Qualitative Research tab in this guide for additional information that may be helpful to authors.

Belgrave, L., D. Zablotsky and M.A. Guadagno.(2002). How do we talk to each other? Writing qualitative research for quantitative readers . Qualitative Health Research , 12(10),1427-1439.

Hunt, Brandon. (2011) Publishing Qualitative Research in Counseling Journals . Journal of Counseling and Development 89(3):296-300.

Fetters, Michael and Dawn Freshwater. (2015). Publishing a Methodological Mixed Methods Research Article. Journal of Mixed Methods Research 9(3): 203-213.

Koch, Lynn C., Tricia Niesz, and Henry McCarthy. (2014). Understanding and Reporting Qualitative Research: An Analytic Review and Recommendations for Submitting Authors. Rehabilitation Counseling Bulletin 57(3):131-143.

Morrow, Susan L. (2005) Quality and Trustworthiness in Qualitative Research in Counseling Psychology ; Journal of Counseling Psychology 52(2):250-260.

Oliver, Deborah P. (2011) "Rigor in Qualitative Research." Research on Aging 33(4): 359-360.

Sandelowski, M., & Leeman, J. (2012). Writing usable qualitative health research findings . Qual Health Res, 22(10), 1404-1413.

Schoenberg, Nancy E., Miller, Edward A., and Pruchno, Rachel. (2011) The qualitative portfolio at The Gerontologist : strong and getting stronger. Gerontologist 51(3): 281-284.

Weaver-Hightower, M. B. (2019). How to write qualitative research . [e-book]

Sidhu, Kalwant, Roger Jones, and Fiona Stevenson (2017). Publishing qualitative research in medical journals. Br J Gen Pract ; 67 (658): 229-230. DOI: 10.3399/bjgp17X690821 PMID: 28450340

• This article is based on a workshop on publishing qualitative studies held at the Society for Academic Primary Care Annual Conference, Dublin, July 2016.

Smith, Mary Lee.(1987) Publishing Qualitative Research. American Educational Research Journal 24(2): 173-183.

Tong, Allison, Sainsbury, Peter, Craig, Jonathan ; Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups , International Journal for Quality in Health Care , Volume 19, Issue 6, 1 December 2007, Pages 349–357, https://doi.org/10.1093/intqhc/mzm042 .

Tracy, Sarah. (2010) Qualitative Quality: Eight 'Big-Tent' Criteria for Excellent Qualitative Research. Qualitative Inquiry 16(10):837-51.

Because reviewers are not always familiar with qualitative methods, they may ask for explanation or justification of your methods when you submit an article. Because different disciplines,different qualitative methods, and different contexts may dictate different approaches to this issue, you may want to consult articles in your field and in target journals for publication.  Additionally, here are some articles that may be helpful in thinking about this issue. 

Bonde, Donna. (2013). Qualitative Interviews: When Enough is Enough . Research by Design.

Guest, Greg, Arwen Bunce, and Laura Johnson. (2006) How Many Interviews are Enough?: An Experiment with Data Saturation and Variability. Field Methods 18(1): 59-82.

Morse, Janice M. (2015) "Data Were Saturated..." Qualitative Health Research 25(5): 587-88 . doi:10.1177/1049732315576699.

Nelson, J. (2016) "Using Conceptual Depth Criteria: Addressing the Challenge of Reaching Saturation in Qualitative Research." Qualitative Research, December. doi:10.1177/1468794116679873.

Patton, Michael Quinn. (2015) "Chapter 5: Designing Qualitative Studies, Module 30 Purposeful Sampling and Case Selection. In Qualitative Research & Evaluation Methods: Integrating Theory and Practice, Fourth edition, pp. 264-72. Thousand Oaks, California: SAGE Publications, Inc. ISBN: 978-1-4129-7212-3

Small, Mario Luis. (2009) 'How Many Cases Do I Need?': On Science and the Logic of Case-Based Selection in Field-Based Research. Ethnography 10(1): 538.

Search the UNC-CH catalog for books about qualitative writing . Selected general books from the catalog are listed below. If you are a researcher at another institution, ask your librarian for assistance locating similar books in your institution's catalog or ordering them via InterLibrary Loan.  

Oft quoted and food for thought

• Morse, J. M. (1997). " Perfectly healthy, but dead": the myth of inter-rater reliability. DOI:10.1177/104973239700700401 Editorial
• Silberzahn, R., Uhlmann, E. L., Martin, D. P., Anselmi, P., Aust, F., Awtrey, E., ... & Carlsson, R. (2018). Many analysts, one data set: Making transparent how variations in analytic choices affect results. Advances in Methods and Practices in Psychologi
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Advanced Research Methods

• Writing a Research Proposal
• What Is Research?
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What Is a Research Proposal?

Reference books.

• Writing the Research Paper
• Presenting the Research Paper

When applying for a research grant or scholarship, or, just before you start a major research project, you may be asked to write a preliminary document that includes basic information about your future research. This is the information that is usually needed in your proposal:

• The topic and goal of the research project.
• The kind of result expected from the research.
• The theory or framework in which the research will be done and presented.
• What kind of methods will be used (statistical, empirical, etc.).
• Short reference on the preliminary scholarship and why your research project is needed; how will it continue/justify/disprove the previous scholarship.
• How much will the research project cost; how will it be budgeted (what for the money will be spent).
• Why is it you who can do this research and not somebody else.

Most agencies that offer scholarships or grants provide information about the required format of the proposal. It may include filling out templates, types of information they need, suggested/maximum length of the proposal, etc.

Research proposal formats vary depending on the size of the planned research, the number of participants, the discipline, the characteristics of the research, etc. The following outline assumes an individual researcher. This is just a SAMPLE; several other ways are equally good and can be successful. If possible, discuss your research proposal with an expert in writing, a professor, your colleague, another student who already wrote successful proposals, etc.

• Author, author's affiliation
• Explain the topic and why you chose it. If possible explain your goal/outcome of the research . How much time you need to complete the research?
• Give a brief summary of previous scholarship and explain why your topic and goals are important.
• Relate your planned research to previous scholarship. What will your research add to our knowledge of the topic.
• Break down the main topic into smaller research questions. List them one by one and explain why these questions need to be investigated. Relate them to previous scholarship.
• Include your hypothesis into the descriptions of the detailed research issues if you have one. Explain why it is important to justify your hypothesis.
• This part depends of the methods conducted in the research process. List the methods; explain how the results will be presented; how they will be assessed.
• Explain what kind of results will justify or  disprove your hypothesis. 
• Explain how much money you need.
• Explain the details of the budget (how much you want to spend for what).
• Describe why your research is important.
• List the sources you have used for writing the research proposal, including a few main citations of the preliminary scholarship.

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• Last Updated: May 16, 2024 10:20 AM
• URL: https://guides.library.ucla.edu/research-methods

Postgraduate students, write your research up with ease!

Are you a postgraduate student and ready to write up your thesis,  dissertation or research report? This template will save you many hours of frustration! Generic functions packaged for your  convenience into a consumer-friendly, ready-to-use template.

Research Write-Up Template

A template for your thesis, dissertation or research report write-up.

Here's what's inside!

The silent film below will show you what the template looks like on the inside.

Professional Look - Ultimate Convenience!

Edit this Microsoft Word Document (docx) to align with the requirements of your tertiary institution.

Generic headings

Generic headings which typically form part of a research report, dissertation or thesis - from the declaration to the appendices.

Title page without page number.

Heading styles

Headings are formatted using the heading styles and multilevel lists functions.

Table of Contents

Automatically generated Table of Contents and auto-update of page numbers with the sections before the Table of Contents to be listed in the Table of Contents.

Page numbers

Page numbers including Roman numerals for the first sections and Arabic numerals for the body of the document.

Lists of Tables

Built in Lists of Tables, Lists of Figures and Lists of Appendices.

Video instructions

Clear instructions through multiple screen recorded videos for hassle-free editing of the template.

Multiple Uses

Save the template in a safe place and reuse it for all future projects.

Section Breaks

Each chapter starts on a new page.

Navigation pane

Tips on how to easily navigate between different sections inside your document using the navigation pane.

Constructing Tables

Instructions on how to give your tables a professional look, add a landscape table to a portrait document and repeat header rows in tables that run over more than one page.

Formatting Figures

Tips on creating and de-identifying images.

Other Tips and Tricks

Other tips and tricks such as how to justify text, create an "outline of your thesis" section and change the size of the margins.

Less frustration and more time to spend on the important things in life.

Research Write-Up Template  

Data analysis write-ups

What should a data-analysis write-up look like.

Writing up the results of a data analysis is not a skill that anyone is born with. It requires practice and, at least in the beginning, a bit of guidance.

Organization

When writing your report, organization will set you free. A good outline is: 1) overview of the problem, 2) your data and modeling approach, 3) the results of your data analysis (plots, numbers, etc), and 4) your substantive conclusions.

1) Overview Describe the problem. What substantive question are you trying to address? This needn’t be long, but it should be clear.

2) Data and model What data did you use to address the question, and how did you do it? When describing your approach, be specific. For example:

• Don’t say, “I ran a regression” when you instead can say, “I fit a linear regression model to predict price that included a house’s size and neighborhood as predictors.”
• Justify important features of your modeling approach. For example: “Neighborhood was included as a categorical predictor in the model because Figure 2 indicated clear differences in price across the neighborhoods.”

Sometimes your Data and Model section will contain plots or tables, and sometimes it won’t. If you feel that a plot helps the reader understand the problem or data set itself—as opposed to your results—then go ahead and include it. A great example here is Tables 1 and 2 in the main paper on the PREDIMED study . These tables help the reader understand some important properties of the data and approach, but not the results of the study itself.

3) Results In your results section, include any figures and tables necessary to make your case. Label them (Figure 1, 2, etc), give them informative captions, and refer to them in the text by their numbered labels where you discuss them. Typical things to include here may include: pictures of the data; pictures and tables that show the fitted model; tables of model coefficients and summaries.

4) Conclusion What did you learn from the analysis? What is the answer, if any, to the question you set out to address?

General advice

Make the sections as short or long as they need to be. For example, a conclusions section is often pretty short, while a results section is usually a bit longer.

It’s OK to use the first person to avoid awkward or bizarre sentence constructions, but try to do so sparingly.

Do not include computer code unless explicitly called for. Note: model outputs do not count as computer code. Outputs should be used as evidence in your results section (ideally formatted in a nice way). By code, I mean the sequence of commands you used to process the data and produce the outputs.

When in doubt, use shorter words and sentences.

A very common way for reports to go wrong is when the writer simply narrates the thought process he or she followed: :First I did this, but it didn’t work. Then I did something else, and I found A, B, and C. I wasn’t really sure what to make of B, but C was interesting, so I followed up with D and E. Then having done this…” Do not do this. The desire for specificity is admirable, but the overall effect is one of amateurism. Follow the recommended outline above.

Here’s a good example of a write-up for an analysis of a few relatively simple problems. Because the problems are so straightforward, there’s not much of a need for an outline of the kind described above. Nonetheless, the spirit of these guidelines is clearly in evidence. Notice the clear exposition, the labeled figures and tables that are referred to in the text, and the careful integration of visual and numerical evidence into the overall argument. This is one worth emulating.

Dissertations and research projects

• Sessions and recordings
• Skill guide
• Finding the gap
• Developing research questions
• Epistemology
• Ethical approval
• Methodology and Methods
• Recruiting participants
• Planning your analysis
• Writing your research proposal
• Hypothesis testing
• Reliability and validity
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You might also want to consult our other sections on  Planning your research  (including Writing your research proposal ),  Quantitative research ,  Qualitative research , and check out the Additional resources .

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Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

• Provide an overview of the research problem and the need for a research methodology section
• Outline the main research questions and objectives

II. Research Design

• Explain the research design chosen and why it is appropriate for the research question(s) and objectives
• Discuss any alternative research designs considered and why they were not chosen
• Describe the research setting and participants (if applicable)

III. Data Collection Methods

• Describe the methods used to collect data (e.g., surveys, interviews, observations)
• Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

• Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
• Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or software used for data analysis

V. Ethical Considerations

• Discuss any ethical issues that may arise from the research and how they were addressed
• Explain how informed consent was obtained (if applicable)
• Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

• Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

• Summarize the key aspects of the research methodology section
• Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

• Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
• Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
• Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
• Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
• Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
• Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
• Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
• Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

• To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
• To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
• To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
• To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
• To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
• To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
• To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
• To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
• To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

• To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
• To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
• To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
• To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
• To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

• Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
• Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
• Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
• Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
• Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
• Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
• Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
• Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Writing a Research Paper

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The Research Paper

There will come a time in most students' careers when they are assigned a research paper. Such an assignment often creates a great deal of unneeded anxiety in the student, which may result in procrastination and a feeling of confusion and inadequacy. This anxiety frequently stems from the fact that many students are unfamiliar and inexperienced with this genre of writing. Never fear—inexperience and unfamiliarity are situations you can change through practice! Writing a research paper is an essential aspect of academics and should not be avoided on account of one's anxiety. In fact, the process of writing a research paper can be one of the more rewarding experiences one may encounter in academics. What is more, many students will continue to do research throughout their careers, which is one of the reasons this topic is so important.

Becoming an experienced researcher and writer in any field or discipline takes a great deal of practice. There are few individuals for whom this process comes naturally. Remember, even the most seasoned academic veterans have had to learn how to write a research paper at some point in their career. Therefore, with diligence, organization, practice, a willingness to learn (and to make mistakes!), and, perhaps most important of all, patience, students will find that they can achieve great things through their research and writing.

The pages in this section cover the following topic areas related to the process of writing a research paper:

• Genre - This section will provide an overview for understanding the difference between an analytical and argumentative research paper.
• Choosing a Topic - This section will guide the student through the process of choosing topics, whether the topic be one that is assigned or one that the student chooses themselves.
• Identifying an Audience - This section will help the student understand the often times confusing topic of audience by offering some basic guidelines for the process.
• Where Do I Begin - This section concludes the handout by offering several links to resources at Purdue, and also provides an overview of the final stages of writing a research paper.

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165Chapter 9 Writing up research

• Published: November 2011
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Writing up your research is as important as undertaking the research itself. It serves as the record of the (hopefully) exhaustive work you have carried out and provides the evidence for your conclusions and interpretations. It is best to anticipate that your paper or thesis should be easy to read by an independent individual who may not have your expertise in the field you are writing about. It should flow, make sense, have structure, and demonstrate originality. Planning your write-up should be considered at the time of planning the project methodology itself, and the process of writing up is best carried out in parallel with the study as it evolves. This chapter will discuss some tips to editing the structure as you go. In general, there is an underlying structure to any write-up, be it a paper in a peer reviewed journal or a thesis. The generally accepted structure is as follows: • Abstract: • Introduction • Methods (or ‘methodology’ or ‘patients and methods’) • Results • Conclusion(s) • Introduction • Methods (or ‘methodology’ or ‘patients and methods’) • Results • Discussion • Conclusion(s) • References or bibliography. These titles are applicable to publications in peer-reviewed journals. Although the structure is universal, the style of write-up is different between writing a paper for a peer-reviewed journal, which requires a clear and concise approach, and a thesis, which needs greater detail. Universities usually have relaxed guidelines regarding the structure of chapters in writing up your thesis (e.g. PhD). However, it is generally advised that however you record your research, the above structure is incorporated into your write-up. For your thesis, there are additional ‘chapter titles’ in the write-up structure you may consider. Below is a comprehensive structured list which, in addition to the core titles (in bold), provides options you may consider to add to your thesis; • Title page • Acknowledgements • Abstract: • Introduction • Methods (or ‘methodology’ or ‘patients and methods’) • Results • Conclusion(s) • Declaration of originality • Table of contents • List of abbreviations • List of tables • List of figures • Introduction • Methods (or ‘methodology’ or ‘patients and methods’) • Results • Discussion • Conclusion(s) • Achievements • Appendices • References/bibliography.

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Writing up qualitative research

There are specific challenges to writing up research based on qualitative data: there is a lot of data to present, complex stories to tell and conclusions that took a long time to develop. But some simple guidelines can help structuring any kind of research output

Daniel Turner

There are specific challenges to writing up research based on qualitative data: there is a lot of data to present, complex stories to tell and conclusions that took a long time to develop. But some simple guidelines can help structuring any kind of research output based on qualitative methods, and help communicate the rich results that come from qualitative data.

There’s a very general statement whenever you are writing or speaking – consider your audience. Who is likely to read your research output? Usually, you would have several from a project, such as a summary for the participants or special interest groups, a research paper for the scientific community (and the journal reviewers) and a thesis which is written to demonstrate knowledge and research skills for an examining panel. Understanding who you are writing for should dictate much of the specifics below, especially how much you need to write to explain certain aspects. Will your readers understand qualitative methodologies? A challenge is often writing for reviewers (or supervisors) who don’t have a qualitative background and don’t understand the methods and small sampling approaches in qualitative research.

This guide is designed to be general enough to apply to a research article or thesis chapter, but note that each will have it’s own specific guidelines for structure and content that should be applied. Some research journals have very specific structures and formatting guidelines to follow, where others allow for more flexibility. Regardless, the key points below should give a general overview of ‘best practice’ in writing up qualitative research.

Theory and Methodology

If you are coming from quantitative disciplines, this is the first section that seems unusual when writing up a research project. Although not explicit, all research has a epistemological and theoretical background and set of assumptions that guide the collection methods and interpretation. However, qualitative research has a strong tradition of making those explicit and justified. The researcher(s) should state their philosophical beliefs on knowledge that have shaped the project.

Describing the epistemology in detail would entail writing about how the researchers see the notion of ‘truth’, positivity, and how much can be understood in the world. Usually this need go no further than adopt one an existing critique or interpretation, such as feminist research methods, or post-positivism. But it should also explain why the qualitative approach was appropriate for this research question, and thus what the appropriate methodology was.

While often connected most clearly to method, the methodology should also touch on the approach selected for analysis and interpretation, noting that adopting something common like grounded theory actually implies a whole series of theoretical and epistemological underpinnings. In a journal article, this will be short: typically only a few sentences, unless the paper is adopting or proposing a new or unusual take on some theoretical stance. But in a qualitative-based thesis, this could well be a chapter in it’s own right.

Finally, researchers should consider some sort of engagement with ‘reflexivity’ and explaining the role and influence of the researcher on the research project. I’ve got a whole article on this , but being open and explicit about the fact that research is not ‘value-free’ and that the background and positionality of the researcher influences the project is usually a key principle in qualitative research.

Methods and analysis

Qualitative methodologies have great variety in the type of methods that can be used, and subtleties as to how they are applied. Therefore it is probably more important to describe the method in detail than in quantitative based research projects, which often have very standard formula for applying tools and measurements. It’s rarely enough to say ‘We interviewed’ or ‘We ran focus groups ’ as these common methods can be applied in many different ways. So specify not just whether you used semi-structured or unstructured interviews, but consider describing the settings, interview guides, and any underlining theoretical or methodological stances.

As a reviewer, I also like to see details of both the sampling and recruitment categories – and as I’ve written before, I think these are distinct and important things. When using the small sample sizes that are hallmarks of most qualitative research, it is especially important to know who these people are, where they are from and how they were selected. Although we might get details about individual respondents lives and backgrounds later, its still important to give an overview of the people who make up the data – just remember it’s not always necessary to reduce these to statistical averages, such as the percentage of people in each age range.

It’s also very important to give a good level of detail about the analytical approach. I’ve written a LOT about this, but suffice it to say that just saying ‘We used grounded theory ’ or ‘We applied thematic analysis ’ is rarely specific enough – again due to the many different ways these terms are interpreted and enacted. Usually the qualitative analysis process is exploratory, non-linear and fraught with missteps and overlapping approaches, so is worthy of more detail. As qualitative research relies so much on the interpretation of the researcher, authors deserve some insight into the analytic process. If using coding, a list of codes, or illustration of some of the main ones can be insightful, even in an appendix.

Another pet hate or mine is papers that just refer to any qualitative analysis software as ‘We analysed the results in Quirkos/Nvivo’. Again, this tells the reader no more useful information than saying ‘We wrote the results using a blue pen’ – it’s not the tool, but how is is applied that affects and defines the analytic approach!

Quoting Data

In the results, findings and discussion sections, a lot of outputs based on qualitative research include extracts from the qualitative data: often from the transcripts from interviews, focus groups , diaries etc. Including quotes like this is a key feature in qualitative research outputs, they give the reader a chance to hear the participants in their own words, giving some validation of the researcher’s own interpretations. They also are effective at illustrating key points in the data and moving on the flow, and providing a framing device for discussing findings. Qualitative software like Quirkos can also help greatly at this stage, helping you keep track of quotes on particular topics, or organised by key quotes so you can quickly find them. However, there is the challenge of the ‘wall of text’.

There is a risk of the paper or chapter becoming over-run with quotations, which coming from different participants with different perspectives can become overwhelming for the reader. In general quotes should be used sparingly, for illustrative snapshots, or colourful instances where the quote says something better than the researcher can. In general, quotes from transcripts won’t be as short and generalisable as a sentence from the writer.

There’s also a temptation to use a quote to prove every conclusion or statement that the author wants to make, in the same way you would have a reference to back up each statement made in a literature review or introduction. But this is rarely necessary, as it will also break the flow of the writing and lead to issues with space and length. The writer should use just enough quotes to establish trust from the reader of their interpretations, saving quotes for when the author is making an important or surprising finding.

There is also the possibility of using two different types of quotes: short in-text quips, and longer multiple-sentence extractions. Shorter quotes are best for using just a few words, or a sentence at most that fits within the discussion. For example, one person may comment, ‘Time is always precious when you have children’. Here it’s not always necessary to attribute the quote to a particular individual (unless what they say is particular to their identity or case).

Longer quotes break the flow of the text, and should usually be formatted as an indented paragraph. These should almost always have a separate line after the quote giving the participant’s number, pseudonym and any relevant information about them, for example age, location or gender if it is relevant to understanding the context of the quote. Usually these should be kept as short as necessary, using … to truncate any sections of the quote that are not relevant. They also need to make sense alone, so any references to ‘it’ or ‘them’ or ‘that’ which are not obvious in the extract should be replaced with a definition in square brackets, for example [my feelings], [my husband] or [my car].

This is even true of other data types, especially pictures. Although most research products like journal articles and theses unfortunately make it very difficult to include audio and video extracts, pictures are possible. Yet these also break the flow of text, and take up a lot of space. They should also be used sparingly, and be well integrated and illustrative of the argument being made.

There can also be additional confidentiality considerations including any multimedia extracts. Text quotations automatically remove the audible voice and face of participants, but this might have to be done manually for participants. Permission to share photos, especially those showing faces and other sensitive or personal situations should also be explicitly sought, ideally for each type of output that might be produced.

Finally, quotes can’t do everything, many important aspects of subtext, and the unspoken (whether non-verbal, or not willing to share) are important context to give the reader. It’s up to the writer to connect the dots, be the expert that was part of the whole process and summarise a huge amount of rich qualitative data into a coherent story.

Discussion and other considerations

Latterly, any output needs to summarise the data and process, and refer back to the research questions and the wider literature. There will often be new questions posed by the data, as well as any conclusions from the data. Finally, consider being honest about what went wrong in the project – either in the data collection stage, or the analysis when theories and assumptions were challenged and changed.

Remember, just as good qualitative research has a story at it’s centre, the same should be true of communicating the findings. Partly it’s a story of the research project (and the role of the researchers in it), but also the story of the respondents – their own journey, experiences and lives. That is why creating a single story that encapsulates a common and differing tales across many participants can be a challenge.

Quirkos is a unique tool for qualitative analysis that helps you explore, manage and discover stories in your qualitative data. We designed it to help us write up our own qualitative data easier and better, and you can try yourself for free right here ! There’s no registration needed for the offline version, and the cloud subscription service lets researchers, work, collaborate and share project data with ease.

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• Research paper

Writing a Research Paper Introduction | Step-by-Step Guide

Published on September 24, 2022 by Jack Caulfield . Revised on March 27, 2023.

The introduction to a research paper is where you set up your topic and approach for the reader. It has several key goals:

• Present your topic and get the reader interested
• Provide background or summarize existing research
• Position your own approach
• Detail your specific research problem and problem statement
• Give an overview of the paper’s structure

The introduction looks slightly different depending on whether your paper presents the results of original empirical research or constructs an argument by engaging with a variety of sources.

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Table of contents

Step 1: introduce your topic, step 2: describe the background, step 3: establish your research problem, step 4: specify your objective(s), step 5: map out your paper, research paper introduction examples, frequently asked questions about the research paper introduction.

The first job of the introduction is to tell the reader what your topic is and why it’s interesting or important. This is generally accomplished with a strong opening hook.

The hook is a striking opening sentence that clearly conveys the relevance of your topic. Think of an interesting fact or statistic, a strong statement, a question, or a brief anecdote that will get the reader wondering about your topic.

For example, the following could be an effective hook for an argumentative paper about the environmental impact of cattle farming:

A more empirical paper investigating the relationship of Instagram use with body image issues in adolescent girls might use the following hook:

Don’t feel that your hook necessarily has to be deeply impressive or creative. Clarity and relevance are still more important than catchiness. The key thing is to guide the reader into your topic and situate your ideas.

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This part of the introduction differs depending on what approach your paper is taking.

In a more argumentative paper, you’ll explore some general background here. In a more empirical paper, this is the place to review previous research and establish how yours fits in.

Argumentative paper: Background information

After you’ve caught your reader’s attention, specify a bit more, providing context and narrowing down your topic.

Provide only the most relevant background information. The introduction isn’t the place to get too in-depth; if more background is essential to your paper, it can appear in the body .

Empirical paper: Describing previous research

For a paper describing original research, you’ll instead provide an overview of the most relevant research that has already been conducted. This is a sort of miniature literature review —a sketch of the current state of research into your topic, boiled down to a few sentences.

This should be informed by genuine engagement with the literature. Your search can be less extensive than in a full literature review, but a clear sense of the relevant research is crucial to inform your own work.

Begin by establishing the kinds of research that have been done, and end with limitations or gaps in the research that you intend to respond to.

The next step is to clarify how your own research fits in and what problem it addresses.

Argumentative paper: Emphasize importance

In an argumentative research paper, you can simply state the problem you intend to discuss, and what is original or important about your argument.

Empirical paper: Relate to the literature

In an empirical research paper, try to lead into the problem on the basis of your discussion of the literature. Think in terms of these questions:

• What research gap is your work intended to fill?
• What limitations in previous work does it address?
• What contribution to knowledge does it make?

You can make the connection between your problem and the existing research using phrases like the following.

Now you’ll get into the specifics of what you intend to find out or express in your research paper.

The way you frame your research objectives varies. An argumentative paper presents a thesis statement, while an empirical paper generally poses a research question (sometimes with a hypothesis as to the answer).

Argumentative paper: Thesis statement

The thesis statement expresses the position that the rest of the paper will present evidence and arguments for. It can be presented in one or two sentences, and should state your position clearly and directly, without providing specific arguments for it at this point.

Empirical paper: Research question and hypothesis

The research question is the question you want to answer in an empirical research paper.

Present your research question clearly and directly, with a minimum of discussion at this point. The rest of the paper will be taken up with discussing and investigating this question; here you just need to express it.

A research question can be framed either directly or indirectly.

• This study set out to answer the following question: What effects does daily use of Instagram have on the prevalence of body image issues among adolescent girls?
• We investigated the effects of daily Instagram use on the prevalence of body image issues among adolescent girls.

If your research involved testing hypotheses , these should be stated along with your research question. They are usually presented in the past tense, since the hypothesis will already have been tested by the time you are writing up your paper.

For example, the following hypothesis might respond to the research question above:

The final part of the introduction is often dedicated to a brief overview of the rest of the paper.

In a paper structured using the standard scientific “introduction, methods, results, discussion” format, this isn’t always necessary. But if your paper is structured in a less predictable way, it’s important to describe the shape of it for the reader.

If included, the overview should be concise, direct, and written in the present tense.

• This paper will first discuss several examples of survey-based research into adolescent social media use, then will go on to …
• This paper first discusses several examples of survey-based research into adolescent social media use, then goes on to …

Full examples of research paper introductions are shown in the tabs below: one for an argumentative paper, the other for an empirical paper.

• Argumentative paper
• Empirical paper

Are cows responsible for climate change? A recent study (RIVM, 2019) shows that cattle farmers account for two thirds of agricultural nitrogen emissions in the Netherlands. These emissions result from nitrogen in manure, which can degrade into ammonia and enter the atmosphere. The study’s calculations show that agriculture is the main source of nitrogen pollution, accounting for 46% of the country’s total emissions. By comparison, road traffic and households are responsible for 6.1% each, the industrial sector for 1%. While efforts are being made to mitigate these emissions, policymakers are reluctant to reckon with the scale of the problem. The approach presented here is a radical one, but commensurate with the issue. This paper argues that the Dutch government must stimulate and subsidize livestock farmers, especially cattle farmers, to transition to sustainable vegetable farming. It first establishes the inadequacy of current mitigation measures, then discusses the various advantages of the results proposed, and finally addresses potential objections to the plan on economic grounds.

The rise of social media has been accompanied by a sharp increase in the prevalence of body image issues among women and girls. This correlation has received significant academic attention: Various empirical studies have been conducted into Facebook usage among adolescent girls (Tiggermann & Slater, 2013; Meier & Gray, 2014). These studies have consistently found that the visual and interactive aspects of the platform have the greatest influence on body image issues. Despite this, highly visual social media (HVSM) such as Instagram have yet to be robustly researched. This paper sets out to address this research gap. We investigated the effects of daily Instagram use on the prevalence of body image issues among adolescent girls. It was hypothesized that daily Instagram use would be associated with an increase in body image concerns and a decrease in self-esteem ratings.

The introduction of a research paper includes several key elements:

• A hook to catch the reader’s interest
• Relevant background on the topic
• Details of your research problem

and your problem statement

• A thesis statement or research question
• Sometimes an overview of the paper

Don’t feel that you have to write the introduction first. The introduction is often one of the last parts of the research paper you’ll write, along with the conclusion.

This is because it can be easier to introduce your paper once you’ve already written the body ; you may not have the clearest idea of your arguments until you’ve written them, and things can change during the writing process .

The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .

A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis —a prediction that will be confirmed or disproved by your research.

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Preparing to Write Survey Questions

Choosing your data type, qualitative.

Data that is verbally based (words and concepts).

Quantitative

Data is numerically based (numbers only).

One survey data type is not necessarily better than another. As summarized by Ahmad (2019), “Quantitative data can help to see the big picture. Qualitative data adds the details.” What type of data you need is going to be dependent on what you are trying to analyze.

Choosing Your Question Format

Open-ended questions.

Open-ended questions are those in which a survey respondent can generate a unique response using their own words. These are seen predominantly in qualitative data surveys. These types of questions are particularly useful when information is needed about individual-specific context that might not be accounted for in a multiple-choice type closed-ended format. A key benefit of open-ended questions is that they allow for respondents to give personalized responses that are not confined to the choice selection set by the researcher. This is simultaneously a key disadvantage, however as it introduces the need for qualitative coding and in turn, introduces a new source of error.

Some examples of open-ended survey questions would be:

• What was your impression about working in groups?

Describe any study techniques you found to be beneficial.

Open-ended survey questions are generally useful for small sample populations. Though these questions offer great insights, on a large sample population scale they are often unfeasible due to the administrative planning and analysis required. If you want the insight from open-ended questions but are working with a large respondent pool, a small sample population can be given an open-ended question-based Pilot Survey to obtain information and inform the design of close-ended question surveys for your larger populations.

Closed-Ended Questions

Closed-ended questions are those in which the response options are limited and provided with the survey. These can be used in qualitative data acquisition as well as quantitative. Some of the main benefits of closed-ended questions are the reduction of the need for communication skills on the behalf of the respondent and the ease of analysis. Conversely, some of the main disadvantages include lack of depth in responses and lack of emergent insights (Hyman and Sierra 2016). These question types help to eliminate sources of error in the data analysis by reducing or eliminating the need to code free response answers; however, the data obtained will be limited to response options generated by the researcher. Closed-ended survey questions can often be evaluated statistically and are easier to use when evaluating large sample sizes, which encourages studies that are more generalizable. Some examples of closed-ended survey questions would be:

• Rewriting Notes
• Group Study
• None of these

Thinking Ahead

Often, qualitative data are linked to open-ended questions while closed-ended questions are paired with quantitative data. The reality is that open-ended qualitative questions can be converted into quantitative data and conversely closed-ended quantitative questions can be used to glean qualitative data. The key is the coding, so write the questions in whichever way will give you the data you are most needing to see while keeping in mind the logistical elements that come along with delivering each type to the population you are studying.

Ahmad, S., Wasim, S., Irfan, S., Gogoi, S., Srivastava, A., & Farheen, Z. (2019). Qualitative v/s. Quantitative Research- A Summarized Review. Journal of Evidence Based Medicine and Healthcare, 6(43).  https://journals.indexcopernicus.com/api/file/viewByFileId/916903.pdf

Hyman, M., & Sierra, J. (2016). Open- versus close-ended survey questions.  NMSU Business Outlook ,  14 (2), 1–5.

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• Statement of Purpose, Personal Statement, and Writing Sample

Details about submitting a statement of purpose, personal statement, and a writing sample as part of your degree program application

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Statement of Purpose 

The statement of purpose is very important to programs when deciding whether to admit a candidate. Your statement should be focused, informative, and convey your research interests and qualifications. You should describe your reasons and motivations for pursuing a graduate degree in your chosen degree program, noting the experiences that shaped your research ambitions, indicating briefly your career objectives, and concisely stating your past work in your intended field of study and in related fields. Your degree program of interest may have specific guidance or requirements for the statement of purpose, so be sure to review the degree program page for more information. Unless otherwise noted, your statement should not exceed 1,000 words. 

Personal Statement

Please describe the personal experiences that led you to pursue graduate education and how these experiences will contribute to the academic environment and/or community in your program or Harvard Griffin GSAS. These may include social and cultural experiences, leadership positions, community engagement, equity and inclusion efforts, other opportunities, or challenges. Your statement should be no longer than 500 words.

Please note that there is no expectation to share detailed sensitive information and you should refrain from including anything that you would not feel at ease sharing. Please also note that the Personal Statement should complement rather than duplicate the content provided in the Statement of Purpose. 

Visit Degree Programs and navigate to your degree program of interest to determine if a Personal Statement is required. The degree program pages will be updated by early September indicating if the Personal Statement is required for your program.

Writing Sample 

Please visit Degree Programs and navigate to your degree program of interest to determine if a writing sample is required. When preparing your writing sample, be sure to follow program requirements, which may include format, topic, or length. 

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