example of research procedure in thesis

Writing the Research Methodology Section of Your Thesis

This article explains the meaning of research methodology and the purpose and importance of writing a research methodology section or chapter for your thesis paper. It discusses what to include and not include in a research methodology section, the different approaches to research methodology that can be used, and the steps involved in writing a robust research methodology section.

What is a thesis research methodology?

A thesis research methodology explains the type of research performed, justifies the methods that you chose   by linking back to the literature review , and describes the data collection and analysis procedures. It is included in your thesis after the Introduction section . Most importantly, this is the section where the readers of your study evaluate its validity and reliability.

What should the research methodology section in your thesis include?

• The aim of your thesis
• An outline of the research methods chosen (qualitative, quantitative, or mixed methods)
• Background and rationale for the methods chosen, explaining why one method was chosen over another
• Methods used for data collection and data analysis
• Materials and equipment used—keep this brief
• Difficulties encountered during data collection and analysis. It is expected that problems will occur during your research process. Use this as an opportunity to demonstrate your problem-solving abilities by explaining how you overcame all obstacles. This builds your readers’ confidence in your study findings.
• A brief evaluation of your research explaining whether your results were conclusive and whether your choice of methodology was effective in practice

What should not be included in the research methodology section of your thesis?

• Irrelevant details, for example, an extensive review of methodologies (this belongs in the literature review section) or information that does not contribute to the readers’ understanding of your chosen methods
• A description of basic procedures
• Excessive details about materials and equipment used. If an extremely long and detailed list is necessary, add it as an appendix

Types of methodological approaches

The choice of which methodological approach to use depends on your field of research and your thesis question. Your methodology should establish a clear relationship with your thesis question and must also be supported by your  literature review . Types of methodological approaches include quantitative, qualitative, or mixed methods. 

Quantitative studies generate data in the form of numbers   to count, classify, measure, or identify relationships or patterns. Information may be collected by performing experiments and tests, conducting surveys, or using existing data. The data are analyzed using  statistical tests and presented as charts or graphs. Quantitative data are typically used in the Sciences domain.

For example, analyzing the effect of a change, such as alterations in electricity consumption by municipalities after installing LED streetlights.

The raw data will need to be prepared for statistical analysis by identifying variables and checking for missing data and outliers. Details of the statistical software program used (name of the package, version number, and supplier name and location) must also be mentioned.

Qualitative studies gather non-numerical data using, for example, observations, focus groups, and in-depth interviews.   Open-ended questions are often posed. This yields rich, detailed, and descriptive results. Qualitative studies are usually   subjective and are helpful for investigating social and cultural phenomena, which are difficult to quantify. Qualitative studies are typically used in the Humanities and Social Sciences (HSS) domain.

For example, determining customer perceptions on the extension of a range of baking utensils to include silicone muffin trays.

The raw data will need to be prepared for analysis by coding and categorizing ideas and themes to interpret the meaning behind the responses given.

Mixed methods use a combination of quantitative and qualitative approaches to present multiple findings about a single phenomenon. T his enables triangulation: verification of the data from two or more sources.

Data collection

Explain the rationale behind the sampling procedure you have chosen. This could involve probability sampling (a random sample from the study population) or non-probability sampling (does not use a random sample).

For quantitative studies, describe the sampling procedure and whether statistical tests were used to determine the  sample size .

Following our example of analyzing the changes in electricity consumption by municipalities after installing LED streetlights, you will need to determine which municipal areas will be sampled and how the information will be gathered (e.g., a physical survey of the streetlights or reviewing purchase orders).

For qualitative research, describe how the participants were chosen and how the data is going to be collected.

Following our example about determining customer perceptions on the extension of a range of baking utensils to include silicone muffin trays, you will need to decide the criteria for inclusion as a study participant (e.g., women aged 20–70 years, bakeries, and bakery supply shops) and how the information will be collected (e.g., interviews, focus groups, online or in-person questionnaires, or video recordings) .

Data analysis

For quantitative research, describe what tests you plan to perform and why you have chosen them. Popular data analysis methods in quantitative research include:

• Descriptive statistics (e.g., means, medians, modes)
• Inferential statistics (e.g., correlation, regression, structural equation modeling)

For qualitative research, describe how the data is going to be analyzed and justify your choice. Popular data analysis methods in qualitative research include:

• Qualitative content analysis
• Thematic analysis
• Discourse analysis
• Narrative analysis
• Grounded theory
• Interpretative phenomenological analysis (IPA)

Evaluate and justify your methodological choices

You need to convince the reader that you have made the correct methodological choices. Once again, this ties back to your thesis question and  literature review . Write using a persuasive tone, and use  rhetoric to convince the reader of the quality, reliability, and validity of your research.

Ethical considerations

• The young researcher should maintain objectivity at all times
• All participants have the right to privacy and anonymity
• Research participation must be voluntary
• All subjects have the right to withdraw from the research at any time
• Consent must be obtained from all participants before starting the research
• Confidentiality of data provided by individuals must be maintained
• Consider how the interpretation and reporting of the data will affect the participants

Tips for writing a robust thesis research methodology

• Determine what kind of knowledge you are trying to uncover. For example, subjective or objective, experimental or interpretive.
• A thorough literature review is the best starting point for choosing your methods.
• Ensure that there is continuity throughout the research process. The authenticity of your research depends upon the validity of the research data, the reliability of your data measurements, and the time taken to conduct the analysis.
• Choose a research method that is achievable. Consider the time and funds available, feasibility, ethics, and access and availability of equipment to measure the phenomenon or answer your thesis question correctly.
• If you are struggling with a concept, ask for help from your supervisor, academic staff members, or fellow students.

A thesis methodology justifies why you have chosen a specific approach to address your thesis question. It explains how you will collect the data and analyze it. Above all, it allows the readers of your study to evaluate its validity and reliability.

A thesis is the most crucial document that you will write during your academic studies. For professional thesis editing and thesis proofreading services, visit  Enago Thesis Editing for more information.

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Introduce your methodological approach , for example, quantitative, qualitative, or mixed methods.

Explain why your chosen approach is relevant to the overall research design and how it links with your  thesis question.

Justify your chosen method and why it is more appropriate than others.

Provide background information on methods that may be unfamiliar to readers of your thesis.

Introduce the tools that you will use for data collection , and explain how you plan to use them (e.g., surveys, interviews, experiments, or existing data).

Explain how you will analyze your results. The type of analysis used depends on the methods you chose. For example, exploring theoretical perspectives to support your explanation of observed behaviors in a qualitative study or using statistical analyses in a quantitative study.

Mention any research limitations. All studies are expected to have limitations, such as the sample size, data collection method, or equipment. Discussing the limitations justifies your choice of methodology despite the risks. It also explains under which conditions the results should be interpreted and shows that you have taken a holistic approach to your study.

What is the difference between methodology and methods? +

Methodology  refers to the overall rationale and strategy of your thesis project. It involves studying the theories or principles behind the methods used in your field so that you can explain why you chose a particular method for your research approach.  Methods , on the other hand, refer to how the data were collected and analyzed (e.g., experiments, surveys, observations, interviews, and statistical tests).

What is the difference between reliability and validity? +

Reliability refers to whether a measurement is consistent (i.e., the results can be reproduced under the same conditions).  Validity refers to whether a measurement is accurate (i.e., the results represent what was supposed to be measured). For example, when investigating linguistic and cultural guidelines for administration of the Preschool Language Scales, Fifth Edition (PLS5) in Arab-American preschool children, the normative sample curves should show the same distribution as a monolingual population, which would indicate that the test is valid. The test would be considered reliable if the results obtained were consistent across different sampling sites.

What tense is used to write the methods section? +

The methods section is written in the past tense because it describes what was done.

What software programs are recommended for statistical analysis? +

Recommended programs include Statistical Analysis Software (SAS) ,  Statistical Package for the Social Sciences (SPSS) ,  JMP ,  R software,  MATLAB , Microsoft Excel,  GraphPad Prism , and  Minitab .

Research Procedures

• Open Access
• First Online: 28 March 2023

Cite this chapter

You have full access to this open access chapter

• Ivan Buljan   ORCID: orcid.org/0000-0002-8719-7277 3  

Part of the book series: Collaborative Bioethics ((CB,volume 1))

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This chapter offers a guide on how to implement good research practices in research procedures, following the logical steps in research planning from idea development to the planning of analysis of collected data and data sharing. This chapter argues that sound research methodology is a foundation for responsible science. At the beginning of each part of the chapter, the subtitles are formulated as questions that may arise during your research process, in the attempt to bring the content closer to the everyday questions you may encounter in research. We hope to stimulate insight into how much we can predict about a research study before it even begins. Research integrity and research ethics are not presented as separate aspects of research planning, but as integral parts that are important from the beginning, and which often set the directions of research activities in the study.

• Research plan
• Research question
• Study design
• Measurement
• Protocol registration
• Reproducibility

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Ethical Issues in Research Methods

Research Integrity: Responsible Conduct of Research

What this chapter is about, case scenario: planning research.

This hypothetical scenario was adapted from a narrative about the process of poor research planning and its consequences. The original case scenario is developed by the Members of The Embassy of Good Science and is available at the Embassy of Good Science . The case is published under the Creative Commons Attribution-ShareAlike License, version 4.0 (CC BY-SA 4.0).

Professor Gallagher is a leader of a research project on moral intuitions in the field of psychology. She is working on the project with Dr. Jones, a philosopher, and Mr. Singh, a doctoral student. Although she has little experience in the matter, Dr. Jones is put as the principal investigator in the study design and analysis of the two experiments, while Mr. Singh prepares materials and conducts the experiments.

After the first experimental study, Mr. Singh sends the results to Dr. Jones for analysis. After some time, eager to enter the results in his thesis, Singh asks Dr. Jones about the results of the study. She admits that she forgot to formulate the hypothesis before data analysis, and now the results can be interpreted as confirmatory, regardless of the direction. They decide to formulate a hypothesis that will result in a positive finding.

Mr. Singh and Dr. Jones present the results to Dr. Gallagher, who is satisfied and proceeds with paper writing. In the second study, Dr. Jones formulates multiple hypotheses before the study begins. Mr. Singh conducts the study and sends the results to Dr. Jones. She performs the analysis by trying to find only significant differences between groups. Finally, to achieve significance, she excludes participants over 60 years from the analysis and while presenting the results, admits that to Prof Gallagher. Prof Galagher is happy about the results and proceeds with the paper writing, while Mr. Singh enters the results in his dissertation.

Before Mr. Singh has the public defense of his dissertation, one of the internal reviewers notices that some data has been excluded from the second study and only significant results were reported. She invites Mr. Singh for an examination board meeting during which MR Singh admits that the data has been excluded and that in the first study hypothesis was formulated after the results were known.

Questions for You

Why is hypothesizing after the results are known, as described in the first study, considered problematic?

What was wrong about reporting only significant results in Study 2?

How would you improve the entire research process described in the scenario?

Good research practice from the European Code of Conduct for Research Integrity:

Researchers take into account the state-of-the-art in developing research ideas.

Researchers make proper and conscientious use of research funds.

What to Do First When You Have an Idea?

It is difficult to come up with a good research idea, and if you struggle to come up with a new research direction, that is perfectly fine. Creative processes are the highest form of learning and developing an idea requires significant cognitive effort. In some cases, you may have an epiphany, where you would suddenly come up with a great idea for your research project. This is something popularized by stereotypes about scientists as eccentric figures who come up with brilliant ways of tackling things using only their intelligence and intuition. However, scientific work resembles ore mining. It takes a tremendous effort to read relevant scientific literature, communicate with your peers, plan, and, in some cases, attempt and fail before you even start digging for gold. As in a mine, you will need to dig a lot of rocks before you come across diamonds and gold.

Usually, the most important decisions are made before digging even begins. To decide where you will start mining, you start with the exploration of the terrain. In research, this means knowing your field of study. You may read an interesting piece in the scientific literature or listen to a presentation at a conference and then think of a hypothesis whose testing will answer an interesting and important question in your research field. On the other hand, sometimes you have to adjust your research interest so that they fit the specific aims of grant funding calls. It does not matter what the source of the idea is, there are always two things to consider when developing research ideas: the current state of the field and the resources available to you. Good research practice is to consider the state of the art in developing your research ideas and make the proper use of research funds. This does not mean that you are not allowed to develop research ideas if they address a research topic that has been neglected. It is the responsibility of a researcher to combine the best of the “old” evidence with new research developments. It is important to keep in mind that research is not performed in a vacuum and that the funds and resources provided by public or private funders are given with an expectation of an honest answer to a specific research question. The main responsibility for the proper use of research funds is on the researcher, and this is overseen by funders during and at the end of the proposal. Another recommendation refers to the use of state-of-the-art information as a basis for your research. The control system in this case is other scientists who read or evaluate your research, and who will recognize outdated research results.

Let’s get back to the analogy of the mine for a moment. If you are paid to dig in the mine, you are expected to find important ore. In our case, a research funder is an employer, and the researchers are workers who need to go down the mine and get their hands dirty in the search for new true information. If you are set to dig a deep hole in the ground with the possibility of finding gold and diamonds, but you do not get any guarantee that you will find them unless you chose an appropriate place in a specific period, you would probably spend a lot of time planning and trying to decide where to start digging, what to do when specific problems arise and to avoid ending with a huge number of worthless rocks instead of gold and diamonds. The process is similar to research planning since a significant amount of the research process can be defined before data collection begins. As valuable as it can be, a research idea is just a thought which needs to be translated into research practice to gain its full impact.

How to Formulate a Good Research Question?

Research is performed to answer a specific question. The research process can be observed as a complex tool that, if used properly, can give a clear answer to a posed question. The research question is the compass of the research process (or the mine if we continue with our mine analogy) since it determines the steps of the research process. It translates into specific research aims and, consequently, into testable research hypotheses. Formulation of a research question is a skill that develops over time, a skill that can be learned. Your research question should have a FINER structure, which stands for: F easible, I nteresting, N ovel, E thical and R elevant. Although initially developed as a set of recommendations for quantitative research, FINER recommendations can be applied to formulating a research question in any given field of science.

The feasibility of a research aim is often defined by time restrictions and funding because research is often burdened by deadlines and output requirements set by the funders. F easibility is also affected by the availability of technology, geographical restrictions, availability of participants, or availability of collaborators. If one considers all those factors, it is obvious that research interests play only a small part in the formulation of a research question. Ask yourself: What research can be published in an excellent journal if you have limited funds and only 1 year for research, with limited access to a specific technology? (Today, highly specialized experts may be a greater problem than the technology in question). You might experience that the formulation of the research question is mostly defined by non-research factors, because, in the end, it is better to have a completed than never-finished research.

There are other elements of the research question that are as important as feasibility. The first one to consider is E thics, which affects all parts of the research process due to its broad nature. If research is not ethical, then it should not be conducted. In a mining analogy, ethics is training and safety, which helps you to protect others and yourself during the entire process. To get back to the best research practices, researchers should make proper use of research funds and fulfill the basic research aim – the benefit to society. This also implies treating members of that society with respect, respecting their privacy and dignity, and being honest and transparent about the research process and results. Therefore, when determining the feasibility of a research study, ethics aspects are the first to consider, along with the objective factors of time, cost, and manpower.

I nterest, N ovelty, and R elevance from the FINER guidance are the elements of the research question that increase the chances of getting funding or the chances for a journal publication, and they are closely aligned. Regardless of the audience (researchers, publishers, non-experts), research should be new to be interesting and relevant. However, doing research just for the novelty’s sake is analogous to the digger who starts digging a new mine every couple of days. It gives you the thrill of a new beginning, but you have not dug deep enough to get to the real results. Relevance, defined in this context as a significant add-on to the current knowledge, can be assessed with a high probability of success by a thorough search for available evidence. The main aim of that process is to identify research or practice gaps that can be filled to improve general knowledge.

Interest is related to the principal internal motivation of an individual to pursue research goals. The interest to pursue research aims is difficult to assess. When planning research, do you consider that research is interesting to you, your peers, potential users, or all three? Probably the last, but here is the catch. Interest is the most subjective part of research planning. Research planning could be understood as a balance between your interest and all other factors that affect the research outcome. A good research idea is often the compromise between objective possibilities and a desire to make a research discovery. If the research idea is interesting but extremely difficult (or even impossible) to conduct in given circumstances, you will end up frustrated. On the other hand, if you decide to perform research based solely on convenience (because it is something for which is easy to get funded or someone is offering you a research topic you are not interested in), it will be very difficult to stay motivated to complete the study.

The more structured your research question is, the easier it is to determine which research design is best to test the hypothesis and statistical analysis is more straightforward. Let’s look at several examples of research questions in biomedical research: Are psychedelics more effective in the treatment of psychosis than the standard treatment? What are the opinions of young fathers on exclusive breastfeeding of their spouses? Which percentage of the population has suffered from post-COVID-19 syndrome? Intuitively, for each of posed research questions, we would try to find answers differently. In cases of comparison of treatment methods and assessment of population percentage, we could express the results quantitatively, e.g., we could state explicitly how much the psychedelics treatment is better compared to standard methods in terms of days of remission or everyday functionality or an explicit number of people in the sample who had COVID-19-related symptoms. On the other hand, the answers to the question about the opinions of young fathers about exclusive breastfeeding are not straightforward or numerical, but more textual and descriptive. It is an example of the research question that would be more suitable for qualitative research. Qualitative and quantitative study designs answer different types of research questions and are therefore suitable for different situations. It is important to carefully consider and choose the most appropriate study design for your research question because only then can you get valid answers.

To conclude, research question development is the crucial factor in setting research direction. Although framed as a single sentence, it defines numerous parts of the research process, from research design to data analysis. On the other hand, non-research factors also have an equal role in research questions and need to be considered.

Literature Search

In a literature search, researchers go through the relevant information sources to systematically collect information, i.e. foreground knowledge, about a specific research phenomenon and/or procedure. While research information is readily available online not only to researchers but to the whole public, the skill of systematic literature search and critical appraisal of evidence is a specific research skill. A literature search is closely tied with the development of the research aim, because you may want to change it after you read about previous research.

When doing a literature search, you must be careful not to omit previous studies about the topic. Here we have two directions that must be balanced. The first one is to do a very precise search to find specific answers, and the other one is to perform a wide, sensitive search that will include many synonyms and combinations of words to discover articles that related to a specific term. Both of those approaches have their advantages and disadvantages: a precise search is less time-consuming and retrieves a small number of studies. However, it may omit important results, so you may end up performing studies for which we already have established conclusions. This creates waste in research because you will spend time and resources, and involve participants in unnecessary work, which would be unethical. You may also miss citing important studies. On the other hand, if you perform a search that is too wide, you will spend a lot of time filtering for useful articles, which leaves less time for doing research.

Researchers design, carry out, analyze and document research in a careful and well-considered manner.

Researchers report their results in a way that is compatible with the standards of the discipline and, where applicable, can be verified and reproduced.

What Is the Optimal Study Design for My Research?

Study designs are one of the main heuristics related to the reader’s perception of the credibility of research information. Also, different study designs give answers to different research questions. It is intuitively easy to understand that different approaches should be taken if the question is about the percentage of infected people in the population vs about which drug is the most effective in the treatment of the disease. The roughest categorization of the study designs is observational and experimental (Box 3.1 ). However, in different scientific areas, even that type of categorization is not enough, since study designs can be theoretical, as in physics or mathematics, or critical, as in humanities, and those types of research will not be covered in this chapter.

Box 3.1 Types of Study Designs

Observational study designs :.

Case study / case series / qualitative study : All three types of study designs take into account a small number of participants and examine the phenomenon of interest in-depth but cannot make generalizations about the entire population.

Case-control study : Individuals with a certain outcome or disease are selected and then information is obtained on whether the subjects have been exposed to the factor under investigation more frequently than the carefully selected controls. This approach is quick and cost-effective in the determination of factors related to specific states (e.g., risk factors), but it relies too much on records and/or self-report, which may be biased.

Cross-sectional study : Best study design for determining the prevalence and examination of relationships between variables that exist in the population at a specific time. Although it is simple to perform, and relatively cheap, it is susceptible to various types of bias related to participant selection, recall bias, and potential differences in group sizes.

Cohort study : Participants are followed over a certain period (retrospectively or prospectively) and data are compared between exposed and unexposed groups to determine predictive factors for the phenomenon of interest.

Experimental study designs :

Randomized controlled trial (RCT) : Participants are allocated to treatment or control groups using randomization procedures to test the strength of the interventions.

Quasi-experimental trial : Participants are allocated to treatment or control groups to test the strengths of the interventions, but there is no randomization procedure.

For some research areas (e.g. health sciences, social sciences), there is another type of research often referred to as evidence synthesis, or literature review. The literature review is a review of evidence-based on a formulated research question and elements. They differ in their scope and methodology (Box 3.2 ).

Box 3.2 Most Common Types of Review

Systematic review : A type of review that searches systematically for, appraises, and synthesizes research evidence, often adhering to guidelines on the conduct of a review.

Scoping review : Type of review which serves as a preliminary assessment of the potential size and scope of available research literature to identify the nature and extent of research evidence (usually including ongoing research).

Meta-analysis : Statistical synthesis of the results from quantitative studies to provide a more precise effect of the results.

Rapid review : A type of review that assesses what is already known about a policy or practice issue, by using systematic review methods to quickly search and critically appraise existing research to inform practical steps.

Umbrella review : Specific type of review that searches and assesses compiling evidence from multiple reviews into one accessible and usable document. Focuses on broad conditions or problems for which there are competing interventions and highlights reviews that address these interventions and their results.

How to Assess which Study Design Is Most Suitable for Your Research Question?

Based on the research aim, one may already get a hint about which study design will be applied, since different study designs give answers to different research questions. However, very often a research question is not so straightforward. Sometimes the research aim could be to determine whether category X is superior to category Y, related to the specific outcome. In those cases, one must determine what the core outcome of the study is (e.g., testing of the effectiveness of two interventions, the scores on current differences between two groups, or the changes over time between different groups), and then it is not difficult to determine the study type in question. In principle, a single research question can be answered with a single study design. However, what we can also use are substitute study designs that can give approximate answers to the question we are asking but will never give as clear an answer as the appropriate design. For example, if we want to explore the reasons early-career researchers seek training in research integrity using a survey approach, we could list all possible answers and say to participants to choose everything that applies to them. The more appropriate study design would be to use a qualitative approach instead because in the survey approach the assumption is that we already know most of the reasons. The survey approach gives us the answer which answer is the most frequent of all. It is a subtle, but important difference. Similarly, although we can test causation using a cohort approach, the evidence for causation is never strong enough in a cohort study as it would be in an experimental study, simply because in a cohort study the researcher does not have control over the independent variable. For example, if we would test the effects of alcohol uptake on the occurrence of cancer, we would compare participants who drink versus those who do not drink to determine the incidence of cancer and make the conclusion about the association between alcohol and cancer. However, the true study design for testing the causation is the randomized controlled trial, where participants are randomized into the interventional and control group, the researcher can give an exact amount of alcohol based on persons’ weight, over a specific period, and in the end, compare the incidence between two groups. However, that type of study would not be an ethical study, so it is not possible to do it. So, there are subtle, but important differences which answer whether can specific and good formulated research questions can be tested and answered fully with only one study design, but due to the various reasons (time restrictions, ethics, cost-benefit analysis) we often use substitute study designs.

When describing people involved in the research process, researchers often refer to them as “participants” or “respondents” (in the case of surveys). A more precise term would be to name the group based on the population they are drawn from (children, people with specific diseases, or people from a specific geographical area). The appropriate term to use would be “participants”, since people are willingly involved in the research process, and the generation of new findings depends on them. Being a participant in a research process means that a person has willingly entered into a research, without any real or imagined coercion, possesses respect and interest for the research topic, with the understanding that positive aspects of research findings encompass the research situation and contribute to general knowledge. This would be a definition of an ideal participant and the researcher should avoid a situation where the participants are coerced to enter research, whether by situational factors or personal reasons because that will probably result in a decrease in motivation for participation and lower quality of research findings. To act ethically and to improve the quality of the research you have to inform participants about the reasons for the study, its purpose, research procedure, their rights, and expected outcomes. A potential pitfall in the research process can happen if all information were not given to participants at the beginning of a research. On the other hand, if a participant enters willingly into the trial, but possesses no real interest in the research topic, it may also affect the motivation for participation in research, because those participants may consider the topic irrelevant and not take the research process seriously (it is easy to imagine a situation where teenagers in a classroom willingly decide to take the survey and participate in research about personality traits, but quickly lose interest after the second page of the questionnaire). All those things are not reflected in the research report but may have an enormous influence on the research findings. Therefore, it is important to define the population of interest and try to motivate participants by providing them with all information before the research begins. Some additional ways to increase participant retention are financial rewards or similar incentives. There are several sampling strategies used when approaching participants for a study (Box 3.3 ).

Box 3.3 Most Common Sampling Methods

Simple random sampling : Each member of the defined population has an equal chance of being included in the study. The sampling is often performed by a coin toss, throwing dice, or (most commonly) using a computer program.

Stratified random sampling : The population of interest is first divided into strata (subgroups) and then we perform random sampling from each subgroup. In this way, the sample with better reflects the target population in specific (relevant) characteristics.

Cluster random sampling : In cluster sampling, the parts of the population (subgroups) are used as sampling units instead of individuals.

Systematic sampling : Participants are selected by equal intervals set before the data collection begins (e.g., every third of every fifth participant who enters the hospital).

Convenience sampling : Participants are approached based on availability. This is perhaps the most common sampling method, especially for survey research.

Purposive sampling : This is the most common approach in qualitative study designs. Researchers choose participants (or they define their characteristics in detail), based on their needs since participants with those special characteristics are the research topic.

It is difficult to give clear criteria on when to stop collecting data. In the case of pre-registered studies, the stopping rule is defined in the protocol. Examples include time restrictions (e.g. 1 month), or the number of participants (e.g. after collecting data on 100 participants). If the research protocol has not been pre-registered, then the stopping rule should be explained in detail in the publication, with reasons. In the latter case, it is never completely clear if the stopping happened after researchers encountered the desired result or if it has been planned. The practice of stopping after you collect sufficient data to support your desired hypothesis is highly unethical since it can lead to biased findings. Therefore, the best way of deciding to terminate the data collection is to pre-register your study, or at least define the desired number of participants by performing sample size calculation before the study begins and pre-registering your study. More about pre-registration and biases which it eliminates will be said later in the chapter.

Ethics of the Sample Size: Too Small and Too Big Samples

A common problem in sampling is that researchers often determine the desired number of participants in a study. The problem is that the response rate is always lower than 100% (in survey research it is often around 15–20%), and a certain percentage of participants drops out of research, resulting in a sample size significantly lower than initially planned. The sample used in research can be too small, and there is a possibility that you will not find a true effect between groups, and in that case, you would make a type II error. The reason is that in small-scale studies the error margin is big, and you would need an extremely large effect size to reach statistical significance. On the other hand, in cases of a big sample, the problem is different. If you have big samples, even small effects will be statistically significant, but the effect size may be negligible. The reason is that within big samples, the margin of error is small, and consequently, every difference is statistically significant. Once again, the proper solution (practically and ethically) for this issue is to calculate the minimum sample size needed to determine the desired difference between groups to avoid the issues with small samples and report effect sizes also, to avoid issues related to (too) big samples.

What We Can and What Cannot Measure?

When it comes to measuring in research, that part is mostly associated with statistical analysis of research data. The principal thing in statistical analysis is to determine the nature of the main outcome variable. In qualitative research (e.g. interview, focus group) or a systematic review without meta-analysis, statistical analysis is not necessary. On the other hand, for quantitative studies (a term often used for mostly case-control, cross-sectional, cohort, and interventional studies) the most important part of the research plan is to define the outcome which can be measured.

In general, there are two types of variables: qualitative and quantitative. When it comes to statistical analysis of qualitative variables (in a statistical context you will encounter the terms nominal and ordinal variables), we can do only basic functions, like counting and comparing the proportions between different groups, but we are not able to calculate mean or standard deviation, because those variables do not possess numerical characteristics. Examples of qualitative variables in research can be the number of surviving patients in a group at the end of the trial, self-reported socioeconomic status as a demographic characteristic, or any binary (yes/no) question in a questionnaire. In some cases, qualitative variables may be coded with numbers, but that does not make them quantitative. A good example is jersey numbers where numbers serve only as a label and not as a measure of quantity (e.g. if you have team player numbers 2, 4, 6, you probably will not state that the average jersey number is 4 because the very concept of the “average” jersey number is absurd). On the other hand, for quantitative variables, differences between numbers indicate the differences in value (e.g. if you say that person X is 1.80 m high, you know that that person is taller than person Y who is 1.70 m tall). You can also calculate different statistical parameters, like mean and median, and dispersion measures, which gives you a more flexible approach in the choice of statistical tests, especially those tests for differences between groups. On the other hand, applying statistical tests would mean that you are more familiar with statistics, which sometimes may present a problem for less (and more) experienced researchers.

When Is the Time to Consult with a Statistician (and Do You Have to)?

Some (lucky) researchers possess sufficient knowledge to perform data analysis themselves. They usually do not need to rely on somebody else to do the statistical analysis for their study. For everybody else, statistical analysis is a crossroad where one needs to decide on including a person with statistical knowledge in a research team or to learn statistical analyses by themselves. The usual process is that the research team defines the research aim, spends time collecting data, collects data, and then tries to find a statistician who will analyse the data. If we keep in mind that research often has high stakes (e.g. doctoral diploma) and researchers are under a great time and financial pressure, the decision to include a statistician is sound and logical, but is it really necessary? The inclusion of a statistician in research when the data are already collected is similar to the situation when you give a cook an already finished stew and ask him/her how it can be improved. The cook may help with the decorations and give some spice which would make the food look and taste better but cannot change the essence of the food since it is already cooked. It is the same with data. The golden rule of statistics is “garbage in, garbage out”, referring to a situation where poorly collected data or data of poor quality will give rise to wrong conclusions. Researchers should know statistics, not only because of the statistical analysis but because statistical reasoning is important in the formulation of measurable research aims. Therefore, statistical analysis is an important part of responsible research and begins with the formulation of the research aim. Statistical experts should be included in the study at that point.

Statisticians usually analyse data based on the initially set research aim. They send back the results of the data analysis to the research team, and they all together (in an ideal scenario) write the manuscript. The dataset remains in the possession of the principal researcher and the paper is published in a journal. Many journals and funders require that the data are publicly available so that anyone can use it, respecting the FAIR principles. Keeping that in mind, the process when somebody else is doing statistical analysis for you requires an enormous level of trust for statisticians, because they can do analysis wrong but you may never know it. Unless, of course, someone else analyses publicly available data and sees the error. In that case, you are also responsible for the analysis because it does not matter that you did not perform it. In some cases, this may lead to the retraction of the paper, which consequently may lead to certain consequences for you (especially if the articles are the basis for a doctoral thesis). If you are willing to put trust in someone to do data analysis, that is perfectly fine, just be aware of this risk, and remember that people make mistakes, very often unintentionally, and therefore a double check by a third party would be recommended.

On the other hand, if you are willing to learn how to do statistical analysis, the good news is that today there are lots of resources to help you. The first thing about statistics you need to know is that you do not need to know all statistics to do statistics. The only knowledge about statistics and statistical programs you need is the one that would help you do the analysis of your research aim and test the research hypothesis. To do that, you will have to see the data you have and search online for ways to analyze a specific problem. You can use tutorials of the statistical program that simultaneously give instructions about the statistical principles and procedures for analysis. Today, most of those programs have online videos and detailed tutorials. Some of those programs are user-friendly and free (e.g., JAMOVI or JASP ), some are commercial (e.g., SPSS, Statistica), and some are less user-friendly but free and available (e.g., R programming language ). If you are a beginner, use a more user-friendly program that has detailed instructions and try to do the statistical analysis by yourself. It is expected that you will make errors, so it would be good if someone more experienced looked at the results and provides feedback on your first attempts.

There are many tutorials on how to do statistical analysis, but far less on how to do proper data entry, which is the preparation of data for statistical analysis. Usually, the data entry table is made in a computer program that provides a tabular view of the data (e.g., Microsoft Excel). The golden rule is that each column represents a variable collected in research, by the order it was collected in the research and that each row represents the unit of the analysis (usually participant, text, article, or any other unit). In a separate sheet or a document, there should be a codebook that contains information about each level of each variable in the dataset, in a way that a person who is not familiar with research can understand the nature of the variable. The codebook should always accompany the dataset, so if the dataset is shared publicly, the codebook should also be shared. The rule of thumb for the data entry is that textual variables are entered as texts and quantitative variables as numbers, and textual variables can later be coded with numbers if necessary. The table for data entry should be made before the research begins, and it is good to seek help from a statistician when defining that, too.

Researchers publish results and interpretations of research in an open, honest, transparent, and accurate manner, and respect the confidentiality of data or findings when legitimately required to do so.

Preregistration of Research Findings

Pre-registration refers to the presentation of the research plan before the research begins. This process serves as the quality control mechanism because it prevents a change in the research hypothesis and methodology to fit the data collected. Pre-registration of research findings should be done after the research has been approved by the ethics committee. There are various registries, some of which are more discipline-specific (e.g., ClinicalTrials.gov for clinical studies) while others are open to different disciplines and study designs (e.g., Open Science Framework ). For the pre-registration of a study, one should clearly define all steps related to the research aim, methods, planned analysis, and planned use of data. Pre-registration of data is nothing more than the public sharing of a research plan. However, even that relatively simple procedure helps eliminate specific biases and decreases the probability of unethical behavior. Pre-registration eliminates the problem of h ypothesizing a fter the r esults are k nown (so-called HARKing) because you need to state your hypothesis publicly before the research begins. Pre-registration should be done before the actual research begins, since you may have already collected the data and modified your hypothesis so that it fits your data (this is called PARKing – p re-registering a fter the r esults are k nown), which should be avoided since it is not a true pre-registration.

Why is pre-registration good for research? When a study is pre-registered, researchers will follow the research plan and planned analysis and will not alter the study protocol and statistical analysis unless there is a valid and strong reason for protocol modification. Many journals today require that studies are pre-registered and that research data are shared. It is recommended to pre-register not only the study aim and methods, planned analysis, but also planned impact, data use, and authorship. When pre-registering authorship, you make clear from the beginning of the study the roles and expectations of each member of the research team. If during the research process some changes happen with the study protocol, those should be clearly explained and pointed out in the final publication, because deviations from the protocol can sometimes bring suspicion in the interpretation of the results if they are not reported. Pre-registration can be peer-reviewed and some problems, which would affect the final interpretation of the results, can be addressed even before the study begins. Finally, when pre-registered, you have the evidence that it was you who came up first with a specific research idea.

One problem that pre-registration cannot prevent is research spin or exaggeration in the scope of study results. Even if data have been carefully collected and properly analyzed, the interpretation of the results is up to the researcher. You should be honest (and modest) when interpreting the results of your study, by stating the true magnitude of your results and putting them in the context of the previous studies.

After the research has been published, the data used in research should be made available to everyone who wants to use them, since data sharing helps research replication and evidence synthesis. You can read more about data sharing in the chapter on Data Management and the chapter on Publication and Dissemination.

With this knowledge in mind, how would you improve the research procedure from the case scenario at the beginning of this chapter?

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Department of Research in Biomedicine and Health and Center for Evidence-based Medicine, University of Split School of Medicine, Split, Croatia

Ivan Buljan

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Ana Marusic

If You Want to Learn More

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Replicability

AllTrials campaign: https://embassy.science/wiki/Theme:0bb5e4f7-9336-4ca8-92e3-c506413d1450

Forensic statistics to detect data fabrication: https://embassy.science/wiki/Theme:467f5cf6-d41f-42a0-9b19-76556579845d

Pre-registration of animal study protocols

Prospective registration of clinical trials

Statistical pre-registration

Data driven hypothesis without disclosure (“HARKing”)

Insufficiently reported study flaws and limitations

Spin of research results .

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Kerr NL (1998) HARKing: hypothesizing after the results are known. Personal Soc Psychol Rev 2(3):196–217. https://doi.org/10.1207/s15327957pspr0203_4

Lipowski EE (2008) Developing great research questions. Am J Health Syst Pharm 65(17):1667–1670. https://doi.org/10.2146/ajhp070276

Onwuegbuzie AJ, Leech NL (2006) Linking research questions to mixed methods data analysis procedures. Qual Rep 11(3):474–498

Rau JL (2004) Searching the literature and selecting the right references. Respir Care 49(10):1242–1245

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Buljan, I. (2023). Research Procedures. In: Marusic, A. (eds) A Guide to Responsible Research. Collaborative Bioethics, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-031-22412-6_3

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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

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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What is a thesis | A Complete Guide with Examples

Table of Contents

A thesis is a comprehensive academic paper based on your original research that presents new findings, arguments, and ideas of your study. It’s typically submitted at the end of your master’s degree or as a capstone of your bachelor’s degree.

However, writing a thesis can be laborious, especially for beginners. From the initial challenge of pinpointing a compelling research topic to organizing and presenting findings, the process is filled with potential pitfalls.

Therefore, to help you, this guide talks about what is a thesis. Additionally, it offers revelations and methodologies to transform it from an overwhelming task to a manageable and rewarding academic milestone.

What is a thesis?

A thesis is an in-depth research study that identifies a particular topic of inquiry and presents a clear argument or perspective about that topic using evidence and logic.

Writing a thesis showcases your ability of critical thinking, gathering evidence, and making a compelling argument. Integral to these competencies is thorough research, which not only fortifies your propositions but also confers credibility to your entire study.

Furthermore, there's another phenomenon you might often confuse with the thesis: the ' working thesis .' However, they aren't similar and shouldn't be used interchangeably.

A working thesis, often referred to as a preliminary or tentative thesis, is an initial version of your thesis statement. It serves as a draft or a starting point that guides your research in its early stages.

As you research more and gather more evidence, your initial thesis (aka working thesis) might change. It's like a starting point that can be adjusted as you learn more. It's normal for your main topic to change a few times before you finalize it.

While a thesis identifies and provides an overarching argument, the key to clearly communicating the central point of that argument lies in writing a strong thesis statement.

What is a thesis statement?

A strong thesis statement (aka thesis sentence) is a concise summary of the main argument or claim of the paper. It serves as a critical anchor in any academic work, succinctly encapsulating the primary argument or main idea of the entire paper.

Typically found within the introductory section, a strong thesis statement acts as a roadmap of your thesis, directing readers through your arguments and findings. By delineating the core focus of your investigation, it offers readers an immediate understanding of the context and the gravity of your study.

Furthermore, an effectively crafted thesis statement can set forth the boundaries of your research, helping readers anticipate the specific areas of inquiry you are addressing.

Different types of thesis statements

A good thesis statement is clear, specific, and arguable. Therefore, it is necessary for you to choose the right type of thesis statement for your academic papers.

Thesis statements can be classified based on their purpose and structure. Here are the primary types of thesis statements:

Argumentative (or Persuasive) thesis statement

Purpose : To convince the reader of a particular stance or point of view by presenting evidence and formulating a compelling argument.

Example : Reducing plastic use in daily life is essential for environmental health.

Analytical thesis statement

Purpose : To break down an idea or issue into its components and evaluate it.

Example : By examining the long-term effects, social implications, and economic impact of climate change, it becomes evident that immediate global action is necessary.

Expository (or Descriptive) thesis statement

Purpose : To explain a topic or subject to the reader.

Example : The Great Depression, spanning the 1930s, was a severe worldwide economic downturn triggered by a stock market crash, bank failures, and reduced consumer spending.

Cause and effect thesis statement

Purpose : To demonstrate a cause and its resulting effect.

Example : Overuse of smartphones can lead to impaired sleep patterns, reduced face-to-face social interactions, and increased levels of anxiety.

Compare and contrast thesis statement

Purpose : To highlight similarities and differences between two subjects.

Example : "While both novels '1984' and 'Brave New World' delve into dystopian futures, they differ in their portrayal of individual freedom, societal control, and the role of technology."

When you write a thesis statement , it's important to ensure clarity and precision, so the reader immediately understands the central focus of your work.

What is the difference between a thesis and a thesis statement?

While both terms are frequently used interchangeably, they have distinct meanings.

A thesis refers to the entire research document, encompassing all its chapters and sections. In contrast, a thesis statement is a brief assertion that encapsulates the central argument of the research.

Here’s an in-depth differentiation table of a thesis and a thesis statement.

Now, to craft a compelling thesis, it's crucial to adhere to a specific structure. Let’s break down these essential components that make up a thesis structure

15 components of a thesis structure

Navigating a thesis can be daunting. However, understanding its structure can make the process more manageable.

Here are the key components or different sections of a thesis structure:

Your thesis begins with the title page. It's not just a formality but the gateway to your research.

Here, you'll prominently display the necessary information about you (the author) and your institutional details.

• Title of your thesis
• Your full name
• Your department
• Your institution and degree program
• Your submission date
• Your Supervisor's name (in some cases)
• Your Department or faculty (in some cases)
• Your University's logo (in some cases)
• Your Student ID (in some cases)

In a concise manner, you'll have to summarize the critical aspects of your research in typically no more than 200-300 words.

This includes the problem statement, methodology, key findings, and conclusions. For many, the abstract will determine if they delve deeper into your work, so ensure it's clear and compelling.

Acknowledgments

Research is rarely a solitary endeavor. In the acknowledgments section, you have the chance to express gratitude to those who've supported your journey.

This might include advisors, peers, institutions, or even personal sources of inspiration and support. It's a personal touch, reflecting the humanity behind the academic rigor.

Table of contents

A roadmap for your readers, the table of contents lists the chapters, sections, and subsections of your thesis.

By providing page numbers, you allow readers to navigate your work easily, jumping to sections that pique their interest.

List of figures and tables

Research often involves data, and presenting this data visually can enhance understanding. This section provides an organized listing of all figures and tables in your thesis.

It's a visual index, ensuring that readers can quickly locate and reference your graphical data.

Introduction

Here's where you introduce your research topic, articulate the research question or objective, and outline the significance of your study.

• Present the research topic : Clearly articulate the central theme or subject of your research.
• Background information : Ground your research topic, providing any necessary context or background information your readers might need to understand the significance of your study.
• Define the scope : Clearly delineate the boundaries of your research, indicating what will and won't be covered.
• Literature review : Introduce any relevant existing research on your topic, situating your work within the broader academic conversation and highlighting where your research fits in.
• State the research Question(s) or objective(s) : Clearly articulate the primary questions or objectives your research aims to address.
• Outline the study's structure : Give a brief overview of how the subsequent sections of your work will unfold, guiding your readers through the journey ahead.

The introduction should captivate your readers, making them eager to delve deeper into your research journey.

Literature review section

Your study correlates with existing research. Therefore, in the literature review section, you'll engage in a dialogue with existing knowledge, highlighting relevant studies, theories, and findings.

It's here that you identify gaps in the current knowledge, positioning your research as a bridge to new insights.

To streamline this process, consider leveraging AI tools. For example, the SciSpace literature review tool enables you to efficiently explore and delve into research papers, simplifying your literature review journey.

Methodology

In the research methodology section, you’ll detail the tools, techniques, and processes you employed to gather and analyze data. This section will inform the readers about how you approached your research questions and ensures the reproducibility of your study.

Here's a breakdown of what it should encompass:

• Research Design : Describe the overall structure and approach of your research. Are you conducting a qualitative study with in-depth interviews? Or is it a quantitative study using statistical analysis? Perhaps it's a mixed-methods approach?
• Data Collection : Detail the methods you used to gather data. This could include surveys, experiments, observations, interviews, archival research, etc. Mention where you sourced your data, the duration of data collection, and any tools or instruments used.
• Sampling : If applicable, explain how you selected participants or data sources for your study. Discuss the size of your sample and the rationale behind choosing it.
• Data Analysis : Describe the techniques and tools you used to process and analyze the data. This could range from statistical tests in quantitative research to thematic analysis in qualitative research.
• Validity and Reliability : Address the steps you took to ensure the validity and reliability of your findings to ensure that your results are both accurate and consistent.
• Ethical Considerations : Highlight any ethical issues related to your research and the measures you took to address them, including — informed consent, confidentiality, and data storage and protection measures.

Moreover, different research questions necessitate different types of methodologies. For instance:

• Experimental methodology : Often used in sciences, this involves a controlled experiment to discern causality.
• Qualitative methodology : Employed when exploring patterns or phenomena without numerical data. Methods can include interviews, focus groups, or content analysis.
• Quantitative methodology : Concerned with measurable data and often involves statistical analysis. Surveys and structured observations are common tools here.
• Mixed methods : As the name implies, this combines both qualitative and quantitative methodologies.

The Methodology section isn’t just about detailing the methods but also justifying why they were chosen. The appropriateness of the methods in addressing your research question can significantly impact the credibility of your findings.

Results (or Findings)

This section presents the outcomes of your research. It's crucial to note that the nature of your results may vary; they could be quantitative, qualitative, or a mix of both.

Quantitative results often present statistical data, showcasing measurable outcomes, and they benefit from tables, graphs, and figures to depict these data points.

Qualitative results , on the other hand, might delve into patterns, themes, or narratives derived from non-numerical data, such as interviews or observations.

Regardless of the nature of your results, clarity is essential. This section is purely about presenting the data without offering interpretations — that comes later in the discussion.

In the discussion section, the raw data transforms into valuable insights.

Start by revisiting your research question and contrast it with the findings. How do your results expand, constrict, or challenge current academic conversations?

Dive into the intricacies of the data, guiding the reader through its implications. Detail potential limitations transparently, signaling your awareness of the research's boundaries. This is where your academic voice should be resonant and confident.

Practical implications (Recommendation) section

Based on the insights derived from your research, this section provides actionable suggestions or proposed solutions.

Whether aimed at industry professionals or the general public, recommendations translate your academic findings into potential real-world actions. They help readers understand the practical implications of your work and how it can be applied to effect change or improvement in a given field.

When crafting recommendations, it's essential to ensure they're feasible and rooted in the evidence provided by your research. They shouldn't merely be aspirational but should offer a clear path forward, grounded in your findings.

The conclusion provides closure to your research narrative.

It's not merely a recap but a synthesis of your main findings and their broader implications. Reconnect with the research questions or hypotheses posited at the beginning, offering clear answers based on your findings.

Reflect on the broader contributions of your study, considering its impact on the academic community and potential real-world applications.

Lastly, the conclusion should leave your readers with a clear understanding of the value and impact of your study.

References (or Bibliography)

Every theory you've expounded upon, every data point you've cited, and every methodological precedent you've followed finds its acknowledgment here.

In references, it's crucial to ensure meticulous consistency in formatting, mirroring the specific guidelines of the chosen citation style .

Proper referencing helps to avoid plagiarism , gives credit to original ideas, and allows readers to explore topics of interest. Moreover, it situates your work within the continuum of academic knowledge.

To properly cite the sources used in the study, you can rely on online citation generator tools  to generate accurate citations!

Here’s more on how you can cite your sources.

Often, the depth of research produces a wealth of material that, while crucial, can make the core content of the thesis cumbersome. The appendix is where you mention extra information that supports your research but isn't central to the main text.

Whether it's raw datasets, detailed procedural methodologies, extended case studies, or any other ancillary material, the appendices ensure that these elements are archived for reference without breaking the main narrative's flow.

For thorough researchers and readers keen on meticulous details, the appendices provide a treasure trove of insights.

Glossary (optional)

In academics, specialized terminologies, and jargon are inevitable. However, not every reader is versed in every term.

The glossary, while optional, is a critical tool for accessibility. It's a bridge ensuring that even readers from outside the discipline can access, understand, and appreciate your work.

By defining complex terms and providing context, you're inviting a wider audience to engage with your research, enhancing its reach and impact.

Remember, while these components provide a structured framework, the essence of your thesis lies in the originality of your ideas, the rigor of your research, and the clarity of your presentation.

As you craft each section, keep your readers in mind, ensuring that your passion and dedication shine through every page.

Thesis examples

To further elucidate the concept of a thesis, here are illustrative examples from various fields:

Example 1 (History): Abolition, Africans, and Abstraction: the Influence of the ‘Noble Savage’ on British and French Antislavery Thought, 1787-1807 by Suchait Kahlon.

Example 2 (Climate Dynamics): Influence of external forcings on abrupt millennial-scale climate changes: a statistical modelling study by Takahito Mitsui · Michel Crucifix

Checklist for your thesis evaluation

Evaluating your thesis ensures that your research meets the standards of academia. Here's an elaborate checklist to guide you through this critical process.

Content and structure

• Is the thesis statement clear, concise, and debatable?
• Does the introduction provide sufficient background and context?
• Is the literature review comprehensive, relevant, and well-organized?
• Does the methodology section clearly describe and justify the research methods?
• Are the results/findings presented clearly and logically?
• Does the discussion interpret the results in light of the research question and existing literature?
• Is the conclusion summarizing the research and suggesting future directions or implications?

Clarity and coherence

• Is the writing clear and free of jargon?
• Are ideas and sections logically connected and flowing?
• Is there a clear narrative or argument throughout the thesis?

Research quality

• Is the research question significant and relevant?
• Are the research methods appropriate for the question?
• Is the sample size (if applicable) adequate?
• Are the data analysis techniques appropriate and correctly applied?
• Are potential biases or limitations addressed?

Originality and significance

• Does the thesis contribute new knowledge or insights to the field?
• Is the research grounded in existing literature while offering fresh perspectives?

Formatting and presentation

• Is the thesis formatted according to institutional guidelines?
• Are figures, tables, and charts clear, labeled, and referenced in the text?
• Is the bibliography or reference list complete and consistently formatted?
• Are appendices relevant and appropriately referenced in the main text?

Grammar and language

• Is the thesis free of grammatical and spelling errors?
• Is the language professional, consistent, and appropriate for an academic audience?
• Are quotations and paraphrased material correctly cited?

Feedback and revision

• Have you sought feedback from peers, advisors, or experts in the field?
• Have you addressed the feedback and made the necessary revisions?

Overall assessment

• Does the thesis as a whole feel cohesive and comprehensive?
• Would the thesis be understandable and valuable to someone in your field?

Ensure to use this checklist to leave no ground for doubt or missed information in your thesis.

After writing your thesis, the next step is to discuss and defend your findings verbally in front of a knowledgeable panel. You’ve to be well prepared as your professors may grade your presentation abilities.

Preparing your thesis defense

A thesis defense, also known as "defending the thesis," is the culmination of a scholar's research journey. It's the final frontier, where you’ll present their findings and face scrutiny from a panel of experts.

Typically, the defense involves a public presentation where you’ll have to outline your study, followed by a question-and-answer session with a committee of experts. This committee assesses the validity, originality, and significance of the research.

The defense serves as a rite of passage for scholars. It's an opportunity to showcase expertise, address criticisms, and refine arguments. A successful defense not only validates the research but also establishes your authority as a researcher in your field.

Here’s how you can effectively prepare for your thesis defense .

Now, having touched upon the process of defending a thesis, it's worth noting that scholarly work can take various forms, depending on academic and regional practices.

One such form, often paralleled with the thesis, is the 'dissertation.' But what differentiates the two?

Dissertation vs. Thesis

Often used interchangeably in casual discourse, they refer to distinct research projects undertaken at different levels of higher education.

To the uninitiated, understanding their meaning might be elusive. So, let's demystify these terms and delve into their core differences.

Here's a table differentiating between the two.

Wrapping up

From understanding the foundational concept of a thesis to navigating its various components, differentiating it from a dissertation, and recognizing the importance of proper citation — this guide covers it all.

As scholars and readers, understanding these nuances not only aids in academic pursuits but also fosters a deeper appreciation for the relentless quest for knowledge that drives academia.

It’s important to remember that every thesis is a testament to curiosity, dedication, and the indomitable spirit of discovery.

Good luck with your thesis writing!

Frequently Asked Questions

A thesis typically ranges between 40-80 pages, but its length can vary based on the research topic, institution guidelines, and level of study.

A PhD thesis usually spans 200-300 pages, though this can vary based on the discipline, complexity of the research, and institutional requirements.

To identify a thesis topic, consider current trends in your field, gaps in existing literature, personal interests, and discussions with advisors or mentors. Additionally, reviewing related journals and conference proceedings can provide insights into potential areas of exploration.

The conceptual framework is often situated in the literature review or theoretical framework section of a thesis. It helps set the stage by providing the context, defining key concepts, and explaining the relationships between variables.

A thesis statement should be concise, clear, and specific. It should state the main argument or point of your research. Start by pinpointing the central question or issue your research addresses, then condense that into a single statement, ensuring it reflects the essence of your paper.

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The Thesis Process

The thesis is an opportunity to work independently on a research project of your own design and contribute to the scholarly literature in your field. You emerge from the thesis process with a solid understanding of how original research is executed and how to best communicate research results. Many students have gone on to publish their research in academic or professional journals.

To ensure affordability, the per-credit tuition rate for the 8-credit thesis is the same as our regular course tuition. There are no additional fees (regular per-credit graduate tuition x 8 credits).

Below are the steps that you need to follow to fulfill the thesis requirement. Please know that through each step, you will receive guidance and mentorship.

1. Determine Your Thesis Topic and Tentative Question

When you have completed between 24 and 32 credits, you work with your assigned research advisor to narrow down your academic interests to a relevant and manageable thesis topic. Log in to MyDCE , then ALB/ALM Community to schedule an appointment with your assigned research advisor via the Degree Candidate Portal.

Thesis Topic Selection

We’ve put together this guide  to help frame your thinking about thesis topic selection.

Every effort is made to support your research interests that are grounded in your ALM course work, but faculty guidance is not available for all possible projects. Therefore, revision or a change of thesis topic may be necessary.

• The point about topic selection is particularly pertinent to scientific research that is dependent upon laboratory space, project funding, and access to private databases. It is also critical for our candidates in ALM, liberal arts fields (English, government, history, international relations, psychology, etc.) who are required to have Harvard faculty direct their thesis projects. Review Harvard’s course catalog online ( my.harvard.edu ) to be sure that there are faculty teaching courses related to your thesis topic. If not, you’ll need to choose an alternative topic.
• Your topic choice must be a new area of research for you. Thesis work represents thoughtful engagement in new academic scholarship. You cannot re-purpose prior research. If you want to draw or expand upon your own previous scholarship for a small portion of your thesis, you need to obtain the explicit permission of your research advisor and cite the work in both the proposal and thesis. Violations of this policy will be referred to the Administrative Board.

2. Prepare Prework for the Crafting the Thesis Proposal (CTP) Course or Tutorial

The next step in the process is to prepare and submit Prework in order to gain registration approval for the Crafting the Thesis Proposal (CTP) tutorial or course. The Prework process ensures that you have done enough prior reading and thinking about your thesis topic to benefit from the CTP.

The CTP provides an essential onramp to the thesis, mapping critical issues of research design, such as scope, relevance to the field, prior scholarly debate, methodology, and perhaps, metrics for evaluating impact as well as bench-marking. The CTP identifies and works through potential hurdles to successful thesis completion, allowing the thesis project to get off to a good start.

In addition to preparing, submitting, and having your Prework approved, to be eligible for the CTP, you need to be in good standing, have completed a minimum of 32 degree-applicable credits, including the statistics/research methods requirement (if pertinent to your field). You also need to have completed Engaging in Scholarly Conversation (if pertinent to your field). If you were admitted after 9/1/2023 Engaging in Scholarly Conversation (A and B) is required, if admitted before 9/1/2023 this series is encouraged.

Advising Note for Biology, Biotechnology, and Bioengineering and Nanotechnology Candidates : Thesis projects in these fields are designed to support ongoing scientific research happening in Harvard University, other academic institutions, or life science industry labs and usually these are done under the direction of a principal investigator (PI). Hence, you need to have a thesis director approved by your research advisor  prior  to submitting CTP prework. Your CTP prework is then framed by the lab’s research. Schedule an appointment with your research advisor a few months in advance of the CTP prework deadlines in order to discuss potential research projects and thesis director assignment.

CTP Prework is sent to our central email box:  [email protected]  between the following firm deadlines:

• April 1 and June 1 for fall CTP
• September 1 and November 1 for spring CTP.  
• August 1 and October 1 for the three-week January session (ALM sustainability candidates only)
• International students who need a student visa to attend Harvard Summer School should submit their prework on January 1, so they can register for the CTP on March 1 and submit timely I-20 paperwork. See international students guidelines for more information.

Your research advisor will provide feedback on your prework submission to gain CTP registration approval.  If your prework is not approved after 3 submissions, your research advisor cannot approve your CTP registration.  If not approved, you’ll need to take additional time for further revisions, and submit new prework during the next CTP prework submission time period for the following term (if your five-year degree completion deadline allows).

3. Register and Successfully Complete the Crafting the Thesis Proposal Tutorial or Course

Once CTP prework is approved, you register for the Crafting the Thesis Proposal (CTP) course or tutorial as you would any other course. The goal of the CTP is to produce a complete, well-written draft of a proposal containing all of the sections required by your research advisor. Creating an academically strong thesis proposal sets the foundation for a high-quality thesis and helps garner the attention of a well-respected thesis director. The proposal is normally between 15 to 25 pages in length.

The CTP  tutorial  is not a course in the traditional sense. You work independently on your proposal with your research advisor by submitting multiple proposal drafts and scheduling individual appointments. You need to make self-directed progress on the proposal without special prompting from the research advisor. You receive a final grade of SAT or UNSAT (failing grade).

The CTP for sustainability is a three-week course in the traditional sense and you receive a letter grade, and it must be B- or higher to receive degree credit for the course.

You are expected to incorporate all of your research advisor’s feedback and be fully committed to producing an academically strong proposal leading to a thesis worthy of a Harvard degree. If you are unable to take advice from your research advisor, follow directions, or produce an acceptable proposal, you will not pass the CTP.

Successful CTP completion also includes a check on the proper use of sources according to our academic integrity guidelines. Violations of our academic integrity policy will be referred to the Administrative Board.

Maximum of two attempts . If you don’t pass that CTP, you’ll have — if your five-year, degree-completion date allows — just one more attempt to complete the CTP before being required to withdraw from the program. If you fail the CTP just once and have no more time to complete the degree, your candidacy will automatically expire. Please note that a WD grade counts as an attempt.

If by not passing the CTP you fall into poor academic standing, you will need to take additional degree-applicable courses to return to good standing before enrolling in the CTP for your second and final time, only if your five-year, degree-completion date allows. If you have no more time on your five-year clock, you will be required to withdraw.

Human Subjects

If your thesis, regardless of field, will involve the use of human subjects (e.g., interviews, surveys, observations), you will need to have your research vetted by the  Committee on the Use of Human Subjects  (CUHS) of Harvard University. Please review the IRB LIFECYCLE GUIDE located on the CUHS website. Your research advisor will help you prepare a draft copy of the project protocol form that you will need to send to CUHS. The vetting process needs to be started during the CTP tutorial, before a thesis director has been assigned.

4. Thesis Director Assignment and Thesis Registration

We expect you to be registered in thesis soon after CTP completion or within 3 months — no later. You cannot delay. It is critical that once a research project has been approved through the CTP process, the project must commence in a timely fashion to ensure the academic integrity of the thesis process.

Once you (1) successfully complete the CTP and (2) have your proposal officially approved by your research advisor (RA), you move to the thesis director assignment phase. Successful completion of the CTP is not the same as having an officially approved proposal. These are two distinct steps.

If you are a life science student (e.g., biology), your thesis director was identified prior to the CTP, and now you need the thesis director to approve the proposal.

The research advisor places you with a thesis director. Do not approach faculty to ask about directing your thesis.  You may suggest names of any potential thesis directors to your research advisor, who will contact them, if they are eligible/available to direct your thesis, after you have an approved thesis proposal.

When a thesis director has been identified or the thesis proposal has been fully vetted by the preassigned life science thesis director, you will receive a letter of authorization from the Assistant Dean of Academic Programs officially approving your thesis work and providing you with instructions on how to register for the eight-credit Master’s Thesis. The letter will also have a tentative graduation date as well as four mandatory thesis submission dates (see Thesis Timetable below).

Continuous Registration Tip: If you want to maintain continued registration from CTP to thesis, you should meet with your RA prior to prework to settle on a workable topic, submit well-documented prework, work diligently throughout the CTP to produce a high-quality proposal that is ready to be matched with a thesis director as soon as the CTP is complete.

Good academic standing. You must be good academic standing to register for the thesis. If not, you’ll need to complete additional courses to bring your GPA up to the 3.0 minimum prior to registration.

Thesis Timetable

The thesis is a 9 to 12 month project that begins after the Crafting the Thesis Proposal (CTP); when your research advisor has approved your proposal and identified a Thesis Director.

The date for the appointment of your Thesis Director determines the graduation cycle that will be automatically assigned to you:

Once registered in the thesis, we will do a 3-month check-in with you and your thesis director to ensure progress is being made. If your thesis director reports little to no progress, the Dean of Academic Programs reserves the right to issue a thesis not complete (TNC) grade (see Thesis Grading below).

As you can see above, you do not submit your thesis all at once at the end, but in four phases: (1) complete draft to TA, (2) final draft to RA for format review and academic integrity check, (3) format approved draft submitted to TA for grading, and (4) upload your 100% complete graded thesis to ETDs.

Due dates for all phases for your assigned graduation cycle cannot be missed.  You must submit materials by the date indicated by 5 PM EST (even if the date falls on a weekend). If you are late, you will not be able to graduate during your assigned cycle.

If you need additional time to complete your thesis after the date it is due to the Thesis Director (phase 1), you need to formally request an extension (which needs to be approved by your Director) by emailing that petition to:  [email protected] .  The maximum allotted time to write your thesis, including any granted extensions of time is 12 months.

Timing Tip: If you want to graduate in May, you should complete the CTP in the fall term two years prior or, if a sustainability student, in the January session one year prior. For example, to graduate in May 2025:

• Complete the CTP in fall 2023 (or in January 2024, if a sustainability student)
• Be assigned a thesis director (TD) in March/April 2024
• Begin the 9-12 month thesis project with TD
• Submit a complete draft of your thesis to your TD by February 1, 2025
• Follow through with all other submission deadlines (April 1, April 15 and May 1 — see table above)
• Graduate in May 2025

5. Conduct Thesis Research

When registered in the thesis, you work diligently and independently, following the advice of your thesis director, in a consistent, regular manner equivalent to full-time academic work to complete the research by your required timeline.

You are required to produce at least 50 pages of text (not including front matter and appendices). Chapter topics (e.g., introduction, background, methods, findings, conclusion) vary by field.

6. Format Review — Required of all Harvard Graduate Students and Part of Your Graduation Requirements

All ALM thesis projects must written in Microsoft Word and follow a specific Harvard University format. A properly formatted thesis is an explicit degree requirement; you cannot graduate without it.

Your research advisor will complete the format review prior to submitting your thesis to your director for final grading according to the Thesis Timetable (see above).

You must use our Microsoft Word ALM Thesis Template or Microsoft ALM Thesis Template Creative Writing (just for creative writing degree candidates). It has all the mandatory thesis formatting built in. Besides saving you a considerable amount of time as you write your thesis, the preprogrammed form ensures that your submitted thesis meets the mandatory style guidelines for margins, font, title page, table of contents, and chapter headings. If you use the template, format review should go smoothly, if not, a delayed graduation is highly likely.

Format review also includes a check on the proper use of sources according to our academic integrity guidelines. Violations of our academic integrity policy will be referred directly to the Administrative Board.

7. Mandatory Thesis Archiving — Required of all Harvard Graduate Students and Part of Your Graduation Requirements

Once your thesis is finalized, meaning that the required grade has been earned and all edits have been completed, you must upload your thesis to Harvard University’s electronic thesis and dissertation submission system (ETDs). Uploading your thesis ETDs is an explicit degree requirement; you cannot graduate without completing this step.

The thesis project will be sent to several downstream systems:

• Your work will be preserved using Harvard’s digital repository DASH (Digital Access to Scholarship at Harvard).
• Metadata about your work will be sent to HOLLIS (the Harvard Library catalog).
• Your work will be preserved in Harvard Library’s DRS2 (digital preservation repository).

By submitting work through ETDs @ Harvard you will be signing the Harvard Author Agreement. This license does not constrain your rights to publish your work subsequently. You retain all intellectual property rights.

For more information on Harvard’s open access initiatives, we recommend you view the Director of the Office of Scholarly Communication (OSC), Peter Suber’s brief introduction .

Thesis Grading

You need to earn a grade of B- or higher in the thesis. All standard course letter grades are available to your thesis director. If you fail to complete substantial work on the thesis, you will earn a grade of TNC (thesis not complete). If you have already earned two withdrawal grades, the TNC grade will count as a zero in your cumulative GPA.

If you earn a grade below B-, you will need to petition the Administrative Board for permission to attempt the thesis for a second and final time. The petition process is only available if you are in good academic standing and your five-year, degree-completion deadline allows for more time. Your candidacy will automatically expire if you do not successfully complete the thesis by your required deadline.

If approved for a second attempt, you may be required to develop a new proposal on a different topic by re-enrolling in the CTP and being assigned a different thesis director. Tuition for the second attempt is calculated at the current year’s rate.

If by not passing the thesis you fall into poor academic standing, you’ll need to take additional degree-applicable courses to return to good standing before re-engaging with the thesis process for the second and final time. This is only an option if your five-year, degree-completion deadline allows for more time.

The Board only reviews cases in which extenuating circumstances prevented the successful completion of the thesis.

Harvard Division of Continuing Education

The Division of Continuing Education (DCE) at Harvard University is dedicated to bringing rigorous academics and innovative teaching capabilities to those seeking to improve their lives through education. We make Harvard education accessible to lifelong learners from high school to retirement.

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Last Updated: Apr 01, 2024 Views: 14

What is a thesis statement.

A thesis statement is a sentence that states the main idea of your paper. It is not just a statement of fact, but a statement of position. What argument are you making about your topic? Your thesis should answer that question.

How long should my thesis statement be?

Thesis statements are often just one sentence. Keep thesis statements concise, without extra words or information. If you are having trouble keeping your thesis statement to one sentence, consider the following:

• Is your thesis is specific enough?
• Does your thesis directly supports your paper?
• Does your thesis accurately describes your purpose or argue your claim?

Can I see some example thesis statements?

The following websites have examples of thesis statements:

• Thesis Statements This link opens in a new window (UNC)
• Tips and Examples for Writing Thesis Statements This link opens in a new window (OWL at Purdue)
• Writing an Effective Thesis Statement This link opens in a new window (Indiana River State College)

These web resources may be helpful if you are looking for examples. However, be sure to evaluate any sources you use! The Shapiro Library cannot vouch for the accuracy of information provided on external websites.

Where can I find more information?

Video tutorials.

• The Persuasive Thesis: How to Write an Argument This link opens in a new window (SNHU Academic Support)
• Research and Citation Playlist This link opens in a new window (SNHU Academic Support)
• Planning a Paper series: Drafting a Thesis Statement This link opens in a new window ( Infobase Learning Cloud - SNHU Login Required)

More Information

• Build a Critical Analysis Thesis This link opens in a new window (SNHU Academic Support)
• Build a Compare & Contrast Thesis This link opens in a new window  (SNHU Academic Support)
• Build a History Thesis This link opens in a new window  (SNHU Academic Support)
• Build a Persuasive Thesis This link opens in a new window  (SNHU Academic Support)

Further Help

This information is intended to be a guideline, not expert advice. Please speak to your instructor about the appropriate way to craft thesis statements for your class assignments and projects.

Campus Students

To access Academic Support, visit your Brightspace course and select “Tutoring and Mentoring” from the Academic Support pulldown menu.

Online Students

To access help with citations and more, visit the Academic Support via modules in Brightspace:

• Academic Support Overview: Getting Help with your Schoolwork This link opens in a new window

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• 10 Research Question Examples to Guide Your Research Project

10 Research Question Examples to Guide your Research Project

Published on October 30, 2022 by Shona McCombes . Revised on October 19, 2023.

The research question is one of the most important parts of your research paper , thesis or dissertation . It’s important to spend some time assessing and refining your question before you get started.

The exact form of your question will depend on a few things, such as the length of your project, the type of research you’re conducting, the topic , and the research problem . However, all research questions should be focused, specific, and relevant to a timely social or scholarly issue.

Once you’ve read our guide on how to write a research question , you can use these examples to craft your own.

Note that the design of your research question can depend on what method you are pursuing. Here are a few options for qualitative, quantitative, and statistical research questions.

Other interesting articles

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

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Research bias

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