how to write chapter 3 in research paper

• Privacy Policy

Home » Dissertation Methodology – Structure, Example and Writing Guide

Dissertation Methodology – Structure, Example and Writing Guide

• Table of Contents

Dissertation Methodology

In any research, the methodology chapter is one of the key components of your dissertation. It provides a detailed description of the methods you used to conduct your research and helps readers understand how you obtained your data and how you plan to analyze it. This section is crucial for replicating the study and validating its results.

Here are the basic elements that are typically included in a dissertation methodology:

• Introduction : This section should explain the importance and goals of your research .
• Research Design : Outline your research approach and why it’s appropriate for your study. You might be conducting an experimental research, a qualitative research, a quantitative research, or a mixed-methods research.
• Data Collection : This section should detail the methods you used to collect your data. Did you use surveys, interviews, observations, etc.? Why did you choose these methods? You should also include who your participants were, how you recruited them, and any ethical considerations.
• Data Analysis : Explain how you intend to analyze the data you collected. This could include statistical analysis, thematic analysis, content analysis, etc., depending on the nature of your study.
• Reliability and Validity : Discuss how you’ve ensured the reliability and validity of your study. For instance, you could discuss measures taken to reduce bias, how you ensured that your measures accurately capture what they were intended to, or how you will handle any limitations in your study.
• Ethical Considerations : This is where you state how you have considered ethical issues related to your research, how you have protected the participants’ rights, and how you have complied with the relevant ethical guidelines.
• Limitations : Acknowledge any limitations of your methodology, including any biases and constraints that might have affected your study.
• Summary : Recap the key points of your methodology chapter, highlighting the overall approach and rationalization of your research.

Types of Dissertation Methodology

The type of methodology you choose for your dissertation will depend on the nature of your research question and the field you’re working in. Here are some of the most common types of methodologies used in dissertations:

Experimental Research

This involves creating an experiment that will test your hypothesis. You’ll need to design an experiment, manipulate variables, collect data, and analyze that data to draw conclusions. This is commonly used in fields like psychology, biology, and physics.

Survey Research

This type of research involves gathering data from a large number of participants using tools like questionnaires or surveys. It can be used to collect a large amount of data and is often used in fields like sociology, marketing, and public health.

Qualitative Research

This type of research is used to explore complex phenomena that can’t be easily quantified. Methods include interviews, focus groups, and observations. This methodology is common in fields like anthropology, sociology, and education.

Quantitative Research

Quantitative research uses numerical data to answer research questions. This can include statistical, mathematical, or computational techniques. It’s common in fields like economics, psychology, and health sciences.

Case Study Research

This type of research involves in-depth investigation of a particular case, such as an individual, group, or event. This methodology is often used in psychology, social sciences, and business.

Mixed Methods Research

This combines qualitative and quantitative research methods in a single study. It’s used to answer more complex research questions and is becoming more popular in fields like social sciences, health sciences, and education.

Action Research

This type of research involves taking action and then reflecting upon the results. This cycle of action-reflection-action continues throughout the study. It’s often used in fields like education and organizational development.

Longitudinal Research

This type of research involves studying the same group of individuals over an extended period of time. This could involve surveys, observations, or experiments. It’s common in fields like psychology, sociology, and medicine.

Ethnographic Research

This type of research involves the in-depth study of people and cultures. Researchers immerse themselves in the culture they’re studying to collect data. This is often used in fields like anthropology and social sciences.

Structure of Dissertation Methodology

The structure of a dissertation methodology can vary depending on your field of study, the nature of your research, and the guidelines of your institution. However, a standard structure typically includes the following elements:

• Introduction : Briefly introduce your overall approach to the research. Explain what you plan to explore and why it’s important.
• Research Design/Approach : Describe your overall research design. This can be qualitative, quantitative, or mixed methods. Explain the rationale behind your chosen design and why it is suitable for your research questions or hypotheses.
• Data Collection Methods : Detail the methods you used to collect your data. You should include what type of data you collected, how you collected it, and why you chose this method. If relevant, you can also include information about your sample population, such as how many people participated, how they were chosen, and any relevant demographic information.
• Data Analysis Methods : Explain how you plan to analyze your collected data. This will depend on the nature of your data. For example, if you collected quantitative data, you might discuss statistical analysis techniques. If you collected qualitative data, you might discuss coding strategies, thematic analysis, or narrative analysis.
• Reliability and Validity : Discuss how you’ve ensured the reliability and validity of your research. This might include steps you took to reduce bias or increase the accuracy of your measurements.
• Ethical Considerations : If relevant, discuss any ethical issues associated with your research. This might include how you obtained informed consent from participants, how you ensured participants’ privacy and confidentiality, or any potential conflicts of interest.
• Limitations : Acknowledge any limitations in your research methodology. This could include potential sources of bias, difficulties with data collection, or limitations in your analysis methods.
• Summary/Conclusion : Briefly summarize the key points of your methodology, emphasizing how it helps answer your research questions or hypotheses.

How to Write Dissertation Methodology

Writing a dissertation methodology requires you to be clear and precise about the way you’ve carried out your research. It’s an opportunity to convince your readers of the appropriateness and reliability of your approach to your research question. Here is a basic guideline on how to write your methodology section:

1. Introduction

Start your methodology section by restating your research question(s) or objective(s). This ensures your methodology directly ties into the aim of your research.

2. Approach

Identify your overall approach: qualitative, quantitative, or mixed methods. Explain why you have chosen this approach.

• Qualitative methods are typically used for exploratory research and involve collecting non-numerical data. This might involve interviews, observations, or analysis of texts.
• Quantitative methods are used for research that relies on numerical data. This might involve surveys, experiments, or statistical analysis.
• Mixed methods use a combination of both qualitative and quantitative research methods.

3. Research Design

Describe the overall design of your research. This could involve explaining the type of study (e.g., case study, ethnography, experimental research, etc.), how you’ve defined and measured your variables, and any control measures you’ve implemented.

4. Data Collection

Explain in detail how you collected your data.

• If you’ve used qualitative methods, you might detail how you selected participants for interviews or focus groups, how you conducted observations, or how you analyzed existing texts.
• If you’ve used quantitative methods, you might detail how you designed your survey or experiment, how you collected responses, and how you ensured your data is reliable and valid.

5. Data Analysis

Describe how you analyzed your data.

• If you’re doing qualitative research, this might involve thematic analysis, discourse analysis, or grounded theory.
• If you’re doing quantitative research, you might be conducting statistical tests, regression analysis, or factor analysis.

Discuss any ethical issues related to your research. This might involve explaining how you obtained informed consent, how you’re protecting participants’ privacy, or how you’re managing any potential harms to participants.

7. Reliability and Validity

Discuss the steps you’ve taken to ensure the reliability and validity of your data.

• Reliability refers to the consistency of your measurements, and you might discuss how you’ve piloted your instruments or used standardized measures.
• Validity refers to the accuracy of your measurements, and you might discuss how you’ve ensured your measures reflect the concepts they’re supposed to measure.

8. Limitations

Every study has its limitations. Discuss the potential weaknesses of your chosen methods and explain any obstacles you faced in your research.

9. Conclusion

Summarize the key points of your methodology, emphasizing how it helps to address your research question or objective.

Example of Dissertation Methodology

An Example of Dissertation Methodology is as follows:

Chapter 3: Methodology

• Introduction

This chapter details the methodology adopted in this research. The study aimed to explore the relationship between stress and productivity in the workplace. A mixed-methods research design was used to collect and analyze data.

Research Design

This study adopted a mixed-methods approach, combining quantitative surveys with qualitative interviews to provide a comprehensive understanding of the research problem. The rationale for this approach is that while quantitative data can provide a broad overview of the relationships between variables, qualitative data can provide deeper insights into the nuances of these relationships.

Data Collection Methods

Quantitative Data Collection : An online self-report questionnaire was used to collect data from participants. The questionnaire consisted of two standardized scales: the Perceived Stress Scale (PSS) to measure stress levels and the Individual Work Productivity Questionnaire (IWPQ) to measure productivity. The sample consisted of 200 office workers randomly selected from various companies in the city.

Qualitative Data Collection : Semi-structured interviews were conducted with 20 participants chosen from the initial sample. The interview guide included questions about participants’ experiences with stress and how they perceived its impact on their productivity.

Data Analysis Methods

Quantitative Data Analysis : Descriptive and inferential statistics were used to analyze the survey data. Pearson’s correlation was used to examine the relationship between stress and productivity.

Qualitative Data Analysis : Interviews were transcribed and subjected to thematic analysis using NVivo software. This process allowed for identifying and analyzing patterns and themes regarding the impact of stress on productivity.

Reliability and Validity

To ensure reliability and validity, standardized measures with good psychometric properties were used. In qualitative data analysis, triangulation was employed by having two researchers independently analyze the data and then compare findings.

Ethical Considerations

All participants provided informed consent prior to their involvement in the study. They were informed about the purpose of the study, their rights as participants, and the confidentiality of their responses.

Limitations

The main limitation of this study is its reliance on self-report measures, which can be subject to biases such as social desirability bias. Moreover, the sample was drawn from a single city, which may limit the generalizability of the findings.

Where to Write Dissertation Methodology

In a dissertation or thesis, the Methodology section usually follows the Literature Review. This placement allows the Methodology to build upon the theoretical framework and existing research outlined in the Literature Review, and precedes the Results or Findings section. Here’s a basic outline of how most dissertations are structured:

• Acknowledgements
• Literature Review (or it may be interspersed throughout the dissertation)
• Methodology
• Results/Findings
• References/Bibliography

In the Methodology chapter, you will discuss the research design, data collection methods, data analysis methods, and any ethical considerations pertaining to your study. This allows your readers to understand how your research was conducted and how you arrived at your results.

Advantages of Dissertation Methodology

The dissertation methodology section plays an important role in a dissertation for several reasons. Here are some of the advantages of having a well-crafted methodology section in your dissertation:

• Clarifies Your Research Approach : The methodology section explains how you plan to tackle your research question, providing a clear plan for data collection and analysis.
• Enables Replication : A detailed methodology allows other researchers to replicate your study. Replication is an important aspect of scientific research because it provides validation of the study’s results.
• Demonstrates Rigor : A well-written methodology shows that you’ve thought critically about your research methods and have chosen the most appropriate ones for your research question. This adds credibility to your study.
• Enhances Transparency : Detailing your methods allows readers to understand the steps you took in your research. This increases the transparency of your study and allows readers to evaluate potential biases or limitations.
• Helps in Addressing Research Limitations : In your methodology section, you can acknowledge and explain the limitations of your research. This is important as it shows you understand that no research method is perfect and there are always potential weaknesses.
• Facilitates Peer Review : A detailed methodology helps peer reviewers assess the soundness of your research design. This is an important part of the publication process if you aim to publish your dissertation in a peer-reviewed journal.
• Establishes the Validity and Reliability : Your methodology section should also include a discussion of the steps you took to ensure the validity and reliability of your measurements, which is crucial for establishing the overall quality of your research.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

Ethical Considerations – Types, Examples and...

What is a Hypothesis – Types, Examples and...

Research Contribution – Thesis Guide

Dissertation – Format, Example and Template

Scope of the Research – Writing Guide and...

Figures in Research Paper – Examples and Guide

Methods Section: Chapter Three

The methods section , or chapter three, of the dissertation or thesis is often the most challenging for graduate students.  The methodology section, chapter three should reiterate the research questions and hypotheses, present the research design, discuss the participants, the instruments to be used, the procedure, the data analysis plan , and the sample size justification.

Research Questions and Null Hypotheses

Chapter three should begin with a portion that discusses the research questions and null hypotheses.  In the research questions and null hypotheses portion of the methodology chapter, the research questions should be restated in statistical language.  For example, “Is there a difference in GPA by gender?” is a t-test type of question, whereas “Is there a relationship between GPA and income level?” is a correlation type of question.  The important thing to remember is to use the language that foreshadows the data analysis plan .  The null hypotheses are just the research questions stated in the null; for example, “There is no difference in GPA by gender,” or “There is no relationship between GPA and income level.”

Research Design

The next portion of the methods section, chapter three is focused on developing the research design.  The research design has several possibilities. First, you must decide if you are doing quantitative, qualitative, or mixed methods research. In a quantitative study, you are assessing participants’ responses on a measure.  For example, participants can endorse their level of agreement on some scale.  A qualitative design is a typically a semi-structured interview which gets transcribed, and the themes among the participants are derived.  A mixed methods project is a mixture of both a quantitative and qualitative study.

Participants

In the research methodology, the participants are typically a sample of the population you want to study.  You are probably not going to study all school children, but you may sample from the population of school children.  You need to include information about the characteristics of the population in your study (Are you sampling all males? teachers with under five years of experience?).  This represents the participants portion of your methods section, chapter three.

Need help with your methods section?

Schedule a time to speak with an expert using the calendar below.

Instruments

The instruments section is a critical part of the methodology section, chapter three.  The instruments section should include the name of the instruments, the scales or subscales, how the scales are computed, and the reliability and validity of the scales.  The instruments portion should have references to the researchers who created the instruments.

The procedure section of the methods chapter is simply how you are going to administer the instruments that you just described to the participants you are going to select.  You should walk the reader through the procedure in detail so that they can replicate your steps and your study.

Data Analysis Plan

The data analysis plan is just that — how you are going to analyze the data when you get the data from your participants.   It includes the statistical tests you are going to use, the statistical assumptions of these tests, and the justification for the statistical tests.

Sample Size Justification

Another important portion of your methods chapter three, is the sample size justification.  Sample size justification (or power analysis) is selecting how many participants you need to have in your study.  The sample size is based on several criteria:  the power you select (which is typically .80), the alpha level selected (which is typically .05), and the effect size (typically, a large or medium effect size is selected).  Importantly, once these criteria are selected, the sample size is going to be based on the type of statistic: an ANOVA is going to have a different sample size calculation than a multiple regression.

• How it works

Chapter 3 – Dissertation Methodology (example)

Disclaimer: This is not a sample of our professional work. The paper has been produced by a student. You can view samples of our work here . Opinions, suggestions, recommendations and results in this piece are those of the author and should not be taken as our company views.

Type of Academic Paper – Dissertation Chapter

Academic Subject – Marketing

Word Count – 3017 words

Introduction

The current chapter presents developing the research methods needed to complete the experimentation portion of the current study. The chapter will discuss in detail the various stages of developing the methodology of the current study. This includes a detailed discussion of the philosophical background of the research method chosen. In addition to this, the chapter describes the data collection strategy, including the selection of research instrumentation and sampling. The chapter closes with a discussion on the analysis tools used to analyse the data collected.

Selecting an Appropriate Research Approach

Creswall (2013) stated that research approaches are plans and procedures that range from steps, including making broad assumptions to detailed methods of data collection, analysis, and interpretation. The several decisions involved in the process are used to decide which approach should be used in a specific study that is informed using philosophical assumptions brought to the study (Creswall 2013). Included in this are procedures of inquiry or research designs and specific research methods used for data collection, its analysis, and finally, its interpretation. However, Guetterman (2015); Lewis (2015); and Creswall (2013) argue that the selection of the specific research approach is based on the nature of the research problem, or the issue that is being addressed by any study, personal experiences of the researchers’, and even the audience for which the study is being developed for.

There are many ways to customise research approaches to develop an approach most suited for a particular study. However, the main three categories with which research approaches are organised include; qualitative, quantitative, and mixed research methods. Creswall (2013) comments that all three approaches are not considered so discrete or distinct from one another. Creswall (2013) states, “qualitative and quantitative approaches should not be viewed as rigid, distinct categories, polar opposite, or dichotomies” (p.32). Newmand and Benz (1998) pointed out that quantitative and qualitative approaches instead represent different ends on a continuum since a study “tends” to be more quantitative than qualitative or vice versa. Lastly, mixed methods research resides in the middle of the continuum as it can incorporate elements and characteristics of both quantitative and qualitative approaches. Lewis (2015) points out that the main distinction that is often cited between quantitative and qualitative research is that it is framed in terms of using numbers rather than words; or using closed-ended questions for quantitative hypotheses over open-ended questions for qualitative interview questions. Guetterman (2015) points out that a clearer way of viewing gradations of differences between the approaches is to examine the basic philosophical assumptions brought to the study, the kinds of research strategies used, and the particular methods implemented in conducting the strategies.

Underlying Philosophical Assumptions

An important component of defining the research approach involves philosophical assumptions that contribute to the broad research approach of planning or proposing to conduct research. It involves the intersection of philosophy, research designs and specific methods as illustrated in Fig. 1 below.

Figure 3.2-1- Research Onion (Source; Saunders and Tosey 2013)

Slife and Williams (1995) have argued that philosophical ideas have remained hidden within the research. However, they still play an influential role in the research practice, and it is for this reason that it is most identified. Various philosophical assumptions are used to construct or develop a study. Saunders et al. (2009) define research philosophy as a belief about how data about a phenomenon should be gathered, analysed and used. Saunders et al. (2009) identify common research philosophies such as positivism, realism, interpretivism, subjectivism, and pragmatism. Dumke (2002) believes that two views, positivism and phenomenology, mainly characterise research philosophy.

Positivism reflects acceptance in adopting the philosophical stance of natural scientists (Saunders, 2003). According to Remenyi et al. (1998), there is a greater preference in working with an “observable social reality” and that the outcome of such research can be “law-like” generalisations that are the same as those which are produced by physical and natural scientists. Gill and Johnson (1997) add that it will also emphasise a high structure methodology to allow for replication for other studies. Dumke (2002) agrees and explains

that a positivist philosophical assumption produces highly structured methodologies and allows for generalisation and quantification of objectives that can be evaluated by statistical methods. For this philosophical approach, the researcher is considered an objective observer who should not be impacted by or impact the subject of research.

On the other hand, more phenomenological approaches agree that the social world of business and management is too complex to develop theories and laws similar to natural sciences. Saunders et al. (2000) argue that this is the reason why reducing observations in the real world to simple laws and generalisations produces a sense of reality which is a bit superficial and doesn’t present the complexity of it.

The current study chooses positivistic assumptions due to the literature review’s discussion of the importance of Big Data in industrial domains and the need for measuring its success in the operations of the business. The current study aims to examine the impact that Big Data has on automobile companies’ operations. To identify a positive relationship between Big Data usage and beneficial business outcomes, the theory needs to be used to generate hypotheses that can later be tested of the relationship which would allow for explanations of laws that can later be assessed (Bryman and Bell, 2015).

Selecting Interpretive Research Approach

Interpretive research approaches are derived from the research philosophy that is adopted. According to Dumke (2002), the two main research approaches are deductive and inductive. The inductive approach is commonly referred to when theory is derived from observations. Thus, the research begins with specific observations and measures. It is then from detecting some pattern that a hypothesis is developed. Dumke (2002) argues that researchers who use an inductive approach usually work with qualitative data and apply various methods to gather specific information that places different views. From the philosophical assumptions discussed in the previous section, it is reasonable to use the deductive approach for the current study. It is also considered the most commonly used theory to establish a relationship between theory and research. The figure below illustrates the steps used for the process of deduction.

Data Collection

• confirmed or rejected
• Revision of theory

Based on what is known about a specific domain, the theoretical considerations encompassing it a hypothesis or hypotheses are deduced that will later be subjected to empirical enquiry (Daum, 2013). Through these hypotheses, concepts of the subject of interest will be translated into entities that are rational for a study. Researchers are then able to deduce their hypotheses and convert them into operational terms.

Hire an Expert Dissertation Chapter Writer

Orders completed by our expert writers are

• Formally drafted in an academic style
• Free Amendments and 100% Plagiarism Free – or your money back!
• 100% Confidential and Timely Delivery!
• Free anti-plagiarism report
• Appreciated by thousands of clients. Check client reviews

Justifying the Use of Quantitative Research Method

Saunders (2003) notes that almost all research will involve some numerical data or even contain data quantified to help a researcher answer their research questions and meet the study’s objectives. However, quantitative data refers to all data that can be a product of all research strategies (Bryman and Bell, 2015; Guetterman, 2015; Lewis, 2015; Saunders, 2003). Based on the philosophical assumptions and interpretive research approach, a quantitative research method is the best suited for the current study. Haq (2014) explains that quantitative research is about collecting numerical data and then analysing it through statistical methods to explain a specific phenomenon. Mujis (2010) defends the use of quantitative research because, unlike qualitative research, which argues that there is no pre-existing reality, quantitative assumes that there is only a single reality about social conditions that researchers cannot influence in any way. Also, qualitative research is commonly used when there is little to no knowledge of a phenomenon, whereas quantitative research is used to find the cause and effect relationship between variables to either verify or nullify some theory or hypothesis (Creswall 2002; Feilzer 2010; Teddlie and Tashakkori 2012).

Selecting an Appropriate Research Strategy

There are many strategies available to implement in a study, as evidenced from Fig. 1. There are many mono-quantitative methods, such as telephone interviews, web-based surveys, postal surveys, and structured questionnaires (Haq 2014). Each instrument has its own pros and cons in terms of quality, time, and data cost. Brymand (2006); Driscoll et al. (2007); Edwards et al. (2002); and Newby et al. (2003) note that most researchers use structured questionnaires for data collection they are unable to control or influence respondents, which leads to low response rates but more accurate data obtained. Saunders and Tosey (2015) have argued that quantitative data is simpler to obtain and more concise to present. Therefore, the current study uses a survey-based questionnaire (See Appendix A).

Justifying the use of Survey Based Questionnaire

Surveys are considered the most traditional forms of research and are used in non-experimental descriptive designs that describe some reality. Survey-based questionnaires are often restricted to a representative sample of a potential group of the study’s interest. In this case, it is the executives currently working for automobile companies in the UK. The survey instrument is then chosen for its effectiveness at being practical and inexpensive (Kelley et al., 2003). Due to the philosophical assumptions, interpretive approach, and methodological approach, the survey design for the current study is considered the best instrument in line with these premises, besides being cost-effective.

Empirical Research Methodology

Research design.

This section describes how research is designed to use the techniques used for data collection, sampling strategy, and data analysis for a quantitative method. Before going into the strategies of data collection and analysis, a set of hypotheses were developed.

Hypotheses Development

The current study uses a quantitative research approach, making it essential to develop a set of hypotheses that will be used as a test standard for the mono-method quantitative design. The following are a set of hypotheses that have been developed from the examination of the literature review.

H1- The greater the company’s budget for Big Data initiatives (More than 1 million GBP), the greater its ability to monetise and generate new revenues.

H2- The greater the company’s budget for Big Data initiatives (More than 1 million GBP) the more decrease in expenses in found.

H3- The greatest impact of Big Data on a company is changing the way business is done.

H4- Big Data integrating with a company has resulted in competitive significance.

H5- The analytical abilities of a company allows for achieved measurable results.

H6- Investing in Big Data will lead to highly successful business results.

H7- A business’s operations function is fuelling Big Data initiatives and effecting change in operations.

H8- The implementation of Big Data in the company has positive impacts on business.

This section includes the sampling method used to collect the number of respondents needed to provide information, then analysed after collection.

Sampling Method

Collis (2009) explains that there are many kinds of sampling methods that can be used for creating a specific target sample from a population. This current study uses simple random sampling to acquire respondents with which the survey will be conducted. Simple random sampling is considered the most basic form of probability sampling. Under the method, elements are taken from the population at random, with all elements having an equal chance of being selected. According to () as of 2014, there are about thirty-five active British car manufacturers in the UK, each having an employee population of 150 or more. This is why the total population of employees in car manufacturers is estimated to be 5,250 employees. The sample, therefore, developed used the following equation;

2  ×   (1 −   )

+(   2 × (1−  ) )  2

Where; N is the population size,  e  is the margin of error (as a decimal),  z  is confidence level (as a z-score), and  p  is percentage value (as a decimal). Thus, the sample size is with a normal distribution of 50%. With the above equation, a population of 5,250; with a 95% confidence level and 5% margin of error, the total sample size needed for the current equals 300. Therefore, N=300, which is the sample size of the current study.

The survey develops (see Appendix A) has a total of three sections, A, B, and C, with a total of 39 questions. Each section has its own set of questions to accomplish. The survey is a mix of closed-end questions that look to comprehend the respondents’ demographic makeup, the Big Data initiatives of the company, and the impact that Big Data was having on their company. The survey is designed to take no longer than twenty minutes. The survey was constructed on Survey Monkey.com, and an online survey provided website. The survey was left on the website for a duration of 40 days to ensure that the maximum number of respondents were able to answer the survey. The only way that the survey was allowed for a respondent is if they passed a security question as if they were working for an automobile company in the UK when taking the survey. Gupta et al. (2004) believe that web surveys are visual stimuli, and the respondent has complete control about whether or how each question is read and understood. That is why Dillman (2000) argued that web questionnaires are expected to resemble those taken through the mail/postal services closely.

Data Analysis

The collected data is then analysed through the Statistical Package for Social Science (SPSS) version 24 for descriptive analysis. The demographic section of the survey will be analysed using descriptive statistics. Further analysis of the data includes regression analysis. Simple regression analysis includes only one independent variable and one dependent variable. Farrar and Glauber (1967) assert that the purpose of regression analysis is to estimate the parameters of dependency, and it should not be used to determine the interdependency of a relationship.

Need a Dissertation Chapter On a Similar Topic?

Conclusions.

The chapter provides a descriptive and in-depth discussion of the methods involved in the current study’s research. The current study is looking towards a quantitative approach that considers positivism as its philosophical undertaking, using deductive reasoning for its interpretive approach, is a mono-quantitative method that involves the use of a survey instrument for data collection. The methodology chapter also provided the data analysis technique, which is descriptive statistics through frequency analysis and regression analysis.

Examples of results;

Question 8- Of these staff, are mostly working in or for your consumer-facing (B2C) businesses, your commercial or wholesale (B2B) businesses, or both?

Based on the illustration, nineteen (19) respondents indicated that 501-1000 employees are dedicated to analytics for both B2B and B2C. The category of using Big Data analytics for both B2B and B2C comprises the most agreement of respondents with 72 of 132 indicated.

The figure above represents the respondents’ answers to their automobile company’s plan for measuring Big Data’s success. Of the 132 participants, 44.70 per cent responded that the company is planning on using quantitative metrics associated with business performance to analyse if Big Data is actually successful. Another, 30.30 per cent indicated that their company was planning on using qualitative metrics tied to business performance. Using business performance to analyse the success of Big Data is coherent to the results of the literature review that indicated previous studies of doing such. As an automobile company, they need to know the results of using Big Data analytics, and that is only by using business performance indicators regardless of being qualitative or quantitative.

Fig. 4.3-6 portrays the response of participants in regards to actually achieving measurable results from Big Data. According to 68.18 per cent of respondents, the company that they worked for did indeed show measurable results from their investments in Big Data. However, 31.82 per cent indicated that there was indeed no measurable result in investing in Big Data.

Bryman, A., Bell, E., 2015. Business Research Methods. Oxford University Press.

Daum, P., 2013. International Synergy Management: A Strategic Approach for Raising Efficiencies in the Cross-border Interaction Process. Anchor Academic Publishing (aap_verlag).

Dümke, R., 2002. Corporate Reputation and its Importance for Business Success: A European

Perspective and its Implication for Public Relations Consultancies. diplom.de.

Guetterman, T.C., 2015. Descriptions of Sampling Practices Within Five Approaches to Qualitative Research in Education and the Health Sciences. Forum Qualitative Sozialforschung /

Forum: Qualitative Social Research 16.

Haq, M., 2014. A Comparative Analysis of Qualitative and Quantitative Research Methods and a Justification for Adopting Mixed Methods in Social Research (PDF Download Available).

ResearchGate 1–22. doi:http://dx.doi.org/10.13140/RG.2.1.1945.8640

Kelley, K., Clark, B., Brown, V., Sitzia, J., 2003. Good practice in the conduct and reporting of survey research. Int J Qual Health Care 15, 261–266. doi:10.1093/intqhc/mzg031

Lewis, S., 2015. Qualitative Inquiry and Research Design: Choosing Among Five Approaches.

Health Promotion Practice 16, 473–475. doi:10.1177/1524839915580941

Saunders, M., 2003. Research Methods for Business Students. Pearson Education India.

Saunders, M.N.K., Tosey, P., 2015. Handbook of Research Methods on Human Resource

Development. Edward Elgar Publishing.

DMCA / Removal Request

If you are the original writer of this Dissertation Chapter and no longer wish to have it published on the www.ResearchProspect.com then please:

Request The Removal Of This Dissertation Chapter

Frequently Asked Questions

How to write methodology chapter of a dissertation.

To write the methodology chapter of a dissertation:

• Describe research design & approach.
• Explain data collection methods.
• Justify chosen methods.
• Address limitations.
• Analyse data.
• Ensure replicability.

USEFUL LINKS

LEARNING RESOURCES

COMPANY DETAILS

• How It Works

How To Write Chapter 3 Of A PhD Thesis Proposal (A Detailed Guide)

The format of a PhD thesis proposal varies from one institution to another. In most cases, however, chapter 3 of the PhD thesis is the research methodology chapter.

This article discusses the main sections of the research methodology chapter and provides tips on how best to write it.

Introduction

Research design, population and sampling, random sampling, non-random sampling, data collection methods and tools, questionnaires, focus group discussions, observation, document review, ethical considerations, data analysis, limitations of the study, final thoughts on how to write chapter 3 of a phd thesis proposal.

The first section is a brief introduction to the chapter, which highlights what the chapter is about.

This section discusses the research design that the study will use. The research design should be guided by the research objectives and research questions the student wants to answer. The research design can be: quantitative, qualitative, or mixed-methods design.

In quantitative research, the study will collect, analyse and present numerical data in the form of statistics. The statistics can be descriptive, inferential, or a mix of both.

In qualitative research, the study collects, analyses and presents data that is in the form of words, opinions, or thoughts of the respondents. Its focus is on the lived-in experiences of the respondents with regard to the problem under investigation.

In mixed-methods research, the study uses a combination of quantitative and qualitative research methods. So some of the research questions render themselves to quantitative research, while others to qualitative research.

Each of these research designs has its pros and cons.

Population of study refers to the entire list of your subjects of interest. If the population is so small, the student can opt to include all the subjects in the study. However, if the population is large, it becomes difficult – both time-wise and resource-wise – to include all the subjects in the study.

A sample is a sub-set of the population of study from which data will be collected to enable the student understand the population.

An example of population vs. sample: Suppose a study aims at investigating the effects of COVID-19 pandemic on micro and small enterprises (MSEs) in Kenya. The population of the study will be all the MSEs in Kenya, which are thousands in number, distributed across the country. It will be impossible for the student to collect data from all those MSEs and therefore a sample will be necessary. The sample size the student decides to use will depend on whether the study is quantitative, qualitative or both. For quantitative studies, a large sample size is necessary, while for qualitative study, the sample size need not be large.

Sampling is the process by which a sample is drawn from a population. There are two categories of sampling techniques, namely: random and non-random sampling. The use of either depends on your research design.

In random sampling, the sample is selected randomly and each subject in the population has an equal chance of being selected for the sample.

The advantage of random sampling is that the results from the sample can be generalised to the population, especially if the sample size is sufficiently large.

Random sampling is used primarily for quantitative studies.

In non-random sampling, the sample is selected deliberately rather than randomly. As a result, the subjects do not have an equal chance of being selected for the sample.

It is also referred to as purposive sampling, meaning that the sample being selected have a specific purpose.

Non-random sampling is used primarily for qualitative sampling.

In this section, the student is expected to discuss in detail the type of data he will collect, that is, whether primary or secondary data (or both) and how he will go about collecting the data from the sample. The methods and tools used also depend on the research design. They include:

Questionnaires are mostly used to collect quantitative data.

Questionnaires are structured in nature and include closed-ended questions.

There are four main types of closed-ended questions used in questionnaires:

• for example: how many children do you have?
• for example: does your household have a radio? 1. Yes 2. No
• for example: what is your highest level of education? 1. No education 2. Primary education 3. Secondary education 4. Tertiary level
• for example: please rate your level of satisfaction with the water services board. 1. Very dissatisfied 2. Dissatisfied 3. Neutral 4. Satisfied 5. Very satisfied

There are two forms of questionnaaire delivery: facilitated questionnaires and self-administered questionnaires.

For facilitated questionnaires, the researcher administers the questionnaire while in self-administered questionnaires, the respondent fills in the questionnaire without the presence of the researcher.

Self-administered questionnaires can be delivered by hand, or mailed via the post office or through email. Facilitated questionnaires can be done either face-to-face or through telephone. Each of these options has its pros and cons.

Interviews are oral discussions between the researcher and the respondent.

Unlike questionnaires, interviews are semi-structured. The researcher uses an interview guide to guide the discussion. The interview guide has some questions that the researcher asks the respondent. However, subsequent questions and discussions are determined by the responses given by the respondent to previous questions.

The flow of interviews will therefore vary from one respondent to another depending on their personalities and openness to responding to the questions.

Whereas interviews are held with individuals, focus group discussions (FGDs) are held with a group of respondents who are key to the problem under investigation.

The participants for an FGD should be selected carefully to represent diverse subjects of the population under investigation.

In the example of the study on the effects of COVID-19 pandemic on micro and small enterprises in Kenya, the student can create a focus group that has the following members: a female-owned enterprise, a male-owned enterprise, a youth-owned enterprise, a family-run enterprise, a non-family-run enterprise, customers of the enterprises, and an employee of the Micro and Small Enterprises Authority (MSEA). Such a focus group would have rich discussions of the views of the different players in the industry.

Observation is also a method of data collection that is commonly used. There are two types of observation: participant observation and non-participant observation.

In participant observation, the researcher immerses himself into the environment of study. In the MSEs study, for example, the researcher would choose to work in one of the enterprises for a period of time where he would observe how the business performs on a day-to-day basis.

In non-participant observation, the researcher removes himself from the environment of study and instead observes from a distance. In the MSEs study, for example, the researcher would go somewhere close to an enterprise and observe how the business performs e.g. how many clients visit the business on a day-to-day basis.

Each observation type has its own pros and cons.

During observation, the researcher should use an observation checklist that guides him on what needs to be observed and the frequency of observation.

In this data collection methods, the student obtains relevant documents to his study and reviews them in-depth. For instance, in the MSEs, the student can review the MSEs Policy of Kenya, Strategic Plan of the Micro and Small Enterprises Authority etc. Such documents are useful in informing the researcher the current state of affairs of the problem under investigation.

This section highlights the ethical considerations that would be followed during the data collection process. The ethical considerations vary from study to study and include:

Consent: the researcher should seek informed consent from the respondent before the data collection begins. For instance, when administering the questionnaire or conducting interviews, the researcher should start by informing the respondent what the study is about, how the respondent was selected, and the benefits of the study and then seek permission to continue with the study. The consent can be in written or oral form.

Compensation for participation: while participating in the study should be voluntary, some research have allowance for monetary compensation. The respondents should be informed of any plans to compensate them but after they have participated in the study, not before.

Confidentiality: the researcher should assure the respondents that their responses will be kept confidential.

Dissemination of the study findings with the respondents: there should be a plan for the student to disseminate the results of the study with the participants, for instance, through validation workshops or written publications.

Additionally, most academic institutions require their students to obtain ethical clearance for their research from the relevant authorities. Students should check if this requirement applies to them and follow the necessary procedure.

In this section, the student should discuss how the data collected will be analysed. Data analysis methods and techniques vary depending on whether the data is quantitative or qualitative.

For quantitative research, the interest of data analysis is the numbers which can be obtained through descriptive statistics and inferential statistics.

Descriptive statistics is usually the first step in analysing quantitative data. There are three categories of descriptive statistics:

• Measures of frequency: frequency table or cross-tabulation table.
• Measures of central tendency: mean, median and mode.
• Measures of variability: range, standard deviation and variance.

Inferential analysis goes a step further and looks at whether the results from the sample can be generalised to the wider population. For studies that involve interventions, inferential analysis is used to check if the intervention has any impact on the population in which it was implemented.

Some inferential analysis techniques include:

• Checking for differences between groups: t-test, analysis of variance (ANOVA) and Chi-square test.
• Checking for correlation or causation between variables: linear regression, logistic regression (logit, probit, multinomial logit/probit models etc).

The choice of data analysis technique will depend on the type of data the student has. For instance, a dependent variable that is continuous will use a different analysis technique from a dependent variable that is categorical in nature. Additionally, the choice of the data analysis technique should be guided by the research questions. The results from the analysis should be able to provide answers to the research questions posed.

For qualitative research, data analysis involves analysing the content of the interviews and focus group discussions. The content can be in different forms such as interview recordings and hand-written notes.

The recordings should be transcribed first and the notes should be organised well before analysis can take place.

The analysis of qualitative data involves coding the data, indexing the data and framing the data to identify the themes that emerge from the data.

Besides discussing the data analysis techniques, the student should discuss the softwares that will be used for analysis. There are many softwares in the market that are used for quantitative (such as SPSS and STATA) and qualitative data (such as NVivo).

The last section in the research methodology chapter discusses the potential limitations of the study and how the limitations will be mitigated. An example of study limitation is low response rate of questionnaires, which can be mitigated through triangulation.

The limitations of the study will vary from one study to another and depend on the context within which the study is conducted.

This article provided a detailed guide on how to write the research methodology chapter of a PhD thesis proposal. The research methodology chapter is informed by the research problem and research questions specified in chapter 1 of the thesis proposal. Students should therefore think through carefully their research study from the beginning because what is in the introduction chapter informs the content in the remaining chapters of the proposal and final thesis.

Related posts

How To Write Chapter 1 Of A PhD Thesis Proposal (A Practical Guide)

How To Write Chapter 2 Of A PhD Thesis Proposal (A Beginner’s Guide)

Grace Njeri-Otieno

Grace Njeri-Otieno is a Kenyan, a wife, a mom, and currently a PhD student, among many other balls she juggles. She holds a Bachelors' and Masters' degrees in Economics and has more than 7 years' experience with an INGO. She was inspired to start this site so as to share the lessons learned throughout her PhD journey with other PhD students. Her vision for this site is "to become a go-to resource center for PhD students in all their spheres of learning."

Recent Content

SPSS Tutorial #12: Partial Correlation Analysis in SPSS

Partial correlation is almost similar to Pearson product-moment correlation only that it accounts for the influence of another variable, which is thought to be correlated with the two variables of...

SPSS Tutorial #11: Correlation Analysis in SPSS

In this post, I discuss what correlation is, the two most common types of correlation statistics used (Pearson and Spearman), and how to conduct correlation analysis in SPSS. What is correlation...

How To Write A Research Paper

Step-By-Step Tutorial With Examples + FREE Template

By: Derek Jansen (MBA) | Expert Reviewer: Dr Eunice Rautenbach | March 2024

For many students, crafting a strong research paper from scratch can feel like a daunting task – and rightly so! In this post, we’ll unpack what a research paper is, what it needs to do , and how to write one – in three easy steps. 🙂 

Overview: Writing A Research Paper

What (exactly) is a research paper.

• How to write a research paper
• Stage 1 : Topic & literature search
• Stage 2 : Structure & outline
• Stage 3 : Iterative writing
• Key takeaways

Let’s start by asking the most important question, “ What is a research paper? ”.

Simply put, a research paper is a scholarly written work where the writer (that’s you!) answers a specific question (this is called a research question ) through evidence-based arguments . Evidence-based is the keyword here. In other words, a research paper is different from an essay or other writing assignments that draw from the writer’s personal opinions or experiences. With a research paper, it’s all about building your arguments based on evidence (we’ll talk more about that evidence a little later).

Now, it’s worth noting that there are many different types of research papers , including analytical papers (the type I just described), argumentative papers, and interpretative papers. Here, we’ll focus on analytical papers , as these are some of the most common – but if you’re keen to learn about other types of research papers, be sure to check out the rest of the blog .

With that basic foundation laid, let’s get down to business and look at how to write a research paper .

Overview: The 3-Stage Process

While there are, of course, many potential approaches you can take to write a research paper, there are typically three stages to the writing process. So, in this tutorial, we’ll present a straightforward three-step process that we use when working with students at Grad Coach.

These three steps are:

• Finding a research topic and reviewing the existing literature
• Developing a provisional structure and outline for your paper, and
• Writing up your initial draft and then refining it iteratively

Let’s dig into each of these.

Need a helping hand?

Step 1: Find a topic and review the literature

As we mentioned earlier, in a research paper, you, as the researcher, will try to answer a question . More specifically, that’s called a research question , and it sets the direction of your entire paper. What’s important to understand though is that you’ll need to answer that research question with the help of high-quality sources – for example, journal articles, government reports, case studies, and so on. We’ll circle back to this in a minute.

The first stage of the research process is deciding on what your research question will be and then reviewing the existing literature (in other words, past studies and papers) to see what they say about that specific research question. In some cases, your professor may provide you with a predetermined research question (or set of questions). However, in many cases, you’ll need to find your own research question within a certain topic area.

Finding a strong research question hinges on identifying a meaningful research gap – in other words, an area that’s lacking in existing research. There’s a lot to unpack here, so if you wanna learn more, check out the plain-language explainer video below.

Once you’ve figured out which question (or questions) you’ll attempt to answer in your research paper, you’ll need to do a deep dive into the existing literature – this is called a “ literature search ”. Again, there are many ways to go about this, but your most likely starting point will be Google Scholar .

If you’re new to Google Scholar, think of it as Google for the academic world. You can start by simply entering a few different keywords that are relevant to your research question and it will then present a host of articles for you to review. What you want to pay close attention to here is the number of citations for each paper – the more citations a paper has, the more credible it is (generally speaking – there are some exceptions, of course).

Ideally, what you’re looking for are well-cited papers that are highly relevant to your topic. That said, keep in mind that citations are a cumulative metric , so older papers will often have more citations than newer papers – just because they’ve been around for longer. So, don’t fixate on this metric in isolation – relevance and recency are also very important.

Beyond Google Scholar, you’ll also definitely want to check out academic databases and aggregators such as Science Direct, PubMed, JStor and so on. These will often overlap with the results that you find in Google Scholar, but they can also reveal some hidden gems – so, be sure to check them out.

Once you’ve worked your way through all the literature, you’ll want to catalogue all this information in some sort of spreadsheet so that you can easily recall who said what, when and within what context. If you’d like, we’ve got a free literature spreadsheet that helps you do exactly that.

Step 2: Develop a structure and outline

With your research question pinned down and your literature digested and catalogued, it’s time to move on to planning your actual research paper .

It might sound obvious, but it’s really important to have some sort of rough outline in place before you start writing your paper. So often, we see students eagerly rushing into the writing phase, only to land up with a disjointed research paper that rambles on in multiple

Now, the secret here is to not get caught up in the fine details . Realistically, all you need at this stage is a bullet-point list that describes (in broad strokes) what you’ll discuss and in what order. It’s also useful to remember that you’re not glued to this outline – in all likelihood, you’ll chop and change some sections once you start writing, and that’s perfectly okay. What’s important is that you have some sort of roadmap in place from the start.

At this stage you might be wondering, “ But how should I structure my research paper? ”. Well, there’s no one-size-fits-all solution here, but in general, a research paper will consist of a few relatively standardised components:

• Introduction
• Literature review
• Methodology

Let’s take a look at each of these.

First up is the introduction section . As the name suggests, the purpose of the introduction is to set the scene for your research paper. There are usually (at least) four ingredients that go into this section – these are the background to the topic, the research problem and resultant research question , and the justification or rationale. If you’re interested, the video below unpacks the introduction section in more detail. 

The next section of your research paper will typically be your literature review . Remember all that literature you worked through earlier? Well, this is where you’ll present your interpretation of all that content . You’ll do this by writing about recent trends, developments, and arguments within the literature – but more specifically, those that are relevant to your research question . The literature review can oftentimes seem a little daunting, even to seasoned researchers, so be sure to check out our extensive collection of literature review content here .

With the introduction and lit review out of the way, the next section of your paper is the research methodology . In a nutshell, the methodology section should describe to your reader what you did (beyond just reviewing the existing literature) to answer your research question. For example, what data did you collect, how did you collect that data, how did you analyse that data and so on? For each choice, you’ll also need to justify why you chose to do it that way, and what the strengths and weaknesses of your approach were.

Now, it’s worth mentioning that for some research papers, this aspect of the project may be a lot simpler . For example, you may only need to draw on secondary sources (in other words, existing data sets). In some cases, you may just be asked to draw your conclusions from the literature search itself (in other words, there may be no data analysis at all). But, if you are required to collect and analyse data, you’ll need to pay a lot of attention to the methodology section. The video below provides an example of what the methodology section might look like.

By this stage of your paper, you will have explained what your research question is, what the existing literature has to say about that question, and how you analysed additional data to try to answer your question. So, the natural next step is to present your analysis of that data . This section is usually called the “results” or “analysis” section and this is where you’ll showcase your findings.

Depending on your school’s requirements, you may need to present and interpret the data in one section – or you might split the presentation and the interpretation into two sections. In the latter case, your “results” section will just describe the data, and the “discussion” is where you’ll interpret that data and explicitly link your analysis back to your research question. If you’re not sure which approach to take, check in with your professor or take a look at past papers to see what the norms are for your programme.

Alright – once you’ve presented and discussed your results, it’s time to wrap it up . This usually takes the form of the “ conclusion ” section. In the conclusion, you’ll need to highlight the key takeaways from your study and close the loop by explicitly answering your research question. Again, the exact requirements here will vary depending on your programme (and you may not even need a conclusion section at all) – so be sure to check with your professor if you’re unsure.

Step 3: Write and refine

Finally, it’s time to get writing. All too often though, students hit a brick wall right about here… So, how do you avoid this happening to you?

Well, there’s a lot to be said when it comes to writing a research paper (or any sort of academic piece), but we’ll share three practical tips to help you get started.

First and foremost , it’s essential to approach your writing as an iterative process. In other words, you need to start with a really messy first draft and then polish it over multiple rounds of editing. Don’t waste your time trying to write a perfect research paper in one go. Instead, take the pressure off yourself by adopting an iterative approach.

Secondly , it’s important to always lean towards critical writing , rather than descriptive writing. What does this mean? Well, at the simplest level, descriptive writing focuses on the “ what ”, while critical writing digs into the “ so what ” – in other words, the implications . If you’re not familiar with these two types of writing, don’t worry! You can find a plain-language explanation here.

Last but not least, you’ll need to get your referencing right. Specifically, you’ll need to provide credible, correctly formatted citations for the statements you make. We see students making referencing mistakes all the time and it costs them dearly. The good news is that you can easily avoid this by using a simple reference manager . If you don’t have one, check out our video about Mendeley, an easy (and free) reference management tool that you can start using today.

Recap: Key Takeaways

We’ve covered a lot of ground here. To recap, the three steps to writing a high-quality research paper are:

• To choose a research question and review the literature
• To plan your paper structure and draft an outline
• To take an iterative approach to writing, focusing on critical writing and strong referencing

Remember, this is just a b ig-picture overview of the research paper development process and there’s a lot more nuance to unpack. So, be sure to grab a copy of our free research paper template to learn more about how to write a research paper.

You Might Also Like:

Can you help me with a full paper template for this Abstract:

Background: Energy and sports drinks have gained popularity among diverse demographic groups, including adolescents, athletes, workers, and college students. While often used interchangeably, these beverages serve distinct purposes, with energy drinks aiming to boost energy and cognitive performance, and sports drinks designed to prevent dehydration and replenish electrolytes and carbohydrates lost during physical exertion.

Objective: To assess the nutritional quality of energy and sports drinks in Egypt.

Material and Methods: A cross-sectional study assessed the nutrient contents, including energy, sugar, electrolytes, vitamins, and caffeine, of sports and energy drinks available in major supermarkets in Cairo, Alexandria, and Giza, Egypt. Data collection involved photographing all relevant product labels and recording nutritional information. Descriptive statistics and appropriate statistical tests were employed to analyze and compare the nutritional values of energy and sports drinks.

Results: The study analyzed 38 sports drinks and 42 energy drinks. Sports drinks were significantly more expensive than energy drinks, with higher net content and elevated magnesium, potassium, and vitamin C. Energy drinks contained higher concentrations of caffeine, sugars, and vitamins B2, B3, and B6.

Conclusion: Significant nutritional differences exist between sports and energy drinks, reflecting their intended uses. However, these beverages’ high sugar content and calorie loads raise health concerns. Proper labeling, public awareness, and responsible marketing are essential to guide safe consumption practices in Egypt.

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

• Print Friendly

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base
• Research paper

How to Create a Structured Research Paper Outline | Example

Published on August 7, 2022 by Courtney Gahan . Revised on August 15, 2023.

A research paper outline is a useful tool to aid in the writing process , providing a structure to follow with all information to be included in the paper clearly organized.

A quality outline can make writing your research paper more efficient by helping to:

• Organize your thoughts
• Understand the flow of information and how ideas are related
• Ensure nothing is forgotten

A research paper outline can also give your teacher an early idea of the final product.

Instantly correct all language mistakes in your text

Upload your document to correct all your mistakes in minutes

Table of contents

Research paper outline example, how to write a research paper outline, formatting your research paper outline, language in research paper outlines.

• Definition of measles
• Rise in cases in recent years in places the disease was previously eliminated or had very low rates of infection
• Figures: Number of cases per year on average, number in recent years. Relate to immunization
• Symptoms and timeframes of disease
• Risk of fatality, including statistics
• How measles is spread
• Immunization procedures in different regions
• Different regions, focusing on the arguments from those against immunization
• Immunization figures in affected regions
• High number of cases in non-immunizing regions
• Illnesses that can result from measles virus
• Fatal cases of other illnesses after patient contracted measles
• Summary of arguments of different groups
• Summary of figures and relationship with recent immunization debate
• Which side of the argument appears to be correct?

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

• Academic style
• Vague sentences
• Style consistency

See an example

Follow these steps to start your research paper outline:

• Decide on the subject of the paper
• Write down all the ideas you want to include or discuss
• Organize related ideas into sub-groups
• Arrange your ideas into a hierarchy: What should the reader learn first? What is most important? Which idea will help end your paper most effectively?
• Create headings and subheadings that are effective
• Format the outline in either alphanumeric, full-sentence or decimal format

There are three different kinds of research paper outline: alphanumeric, full-sentence and decimal outlines. The differences relate to formatting and style of writing.

• Alphanumeric
• Full-sentence

An alphanumeric outline is most commonly used. It uses Roman numerals, capitalized letters, arabic numerals, lowercase letters to organize the flow of information. Text is written with short notes rather than full sentences.

• Sub-point of sub-point 1

Essentially the same as the alphanumeric outline, but with the text written in full sentences rather than short points.

• Additional sub-point to conclude discussion of point of evidence introduced in point A

A decimal outline is similar in format to the alphanumeric outline, but with a different numbering system: 1, 1.1, 1.2, etc. Text is written as short notes rather than full sentences.

• 1.1.1 Sub-point of first point
• 1.1.2 Sub-point of first point
• 1.2 Second point

To write an effective research paper outline, it is important to pay attention to language. This is especially important if it is one you will show to your teacher or be assessed on.

There are four main considerations: parallelism, coordination, subordination and division.

Parallelism: Be consistent with grammatical form

Parallel structure or parallelism is the repetition of a particular grammatical form within a sentence, or in this case, between points and sub-points. This simply means that if the first point is a verb , the sub-point should also be a verb.

Example of parallelism:

• Include different regions, focusing on the different arguments from those against immunization

Coordination: Be aware of each point’s weight

Your chosen subheadings should hold the same significance as each other, as should all first sub-points, secondary sub-points, and so on.

Example of coordination:

• Include immunization figures in affected regions
• Illnesses that can result from the measles virus

Subordination: Work from general to specific

Subordination refers to the separation of general points from specific. Your main headings should be quite general, and each level of sub-point should become more specific.

Example of subordination:

Division: break information into sub-points.

Your headings should be divided into two or more subsections. There is no limit to how many subsections you can include under each heading, but keep in mind that the information will be structured into a paragraph during the writing stage, so you should not go overboard with the number of sub-points.

Ready to start writing or looking for guidance on a different step in the process? Read our step-by-step guide on how to write a research paper .

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Gahan, C. (2023, August 15). How to Create a Structured Research Paper Outline | Example. Scribbr. Retrieved June 24, 2024, from https://www.scribbr.com/research-paper/outline/

Is this article helpful?

Courtney Gahan

Other students also liked, research paper format | apa, mla, & chicago templates, writing a research paper introduction | step-by-step guide, writing a research paper conclusion | step-by-step guide, get unlimited documents corrected.

✔ Free APA citation check included ✔ Unlimited document corrections ✔ Specialized in correcting academic texts

Last updated 27/06/24: Online ordering is currently unavailable due to technical issues. We apologise for any delays responding to customers while we resolve this. For further updates please visit our website: https://www.cambridge.org/news-and-insights/technical-incident

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings .

Login Alert

• > How to Do Research
• > Write the proposal

Book contents

• Frontmatter
• Acknowledgements
• Introduction: Types of research
• Part 1 The research process
• 1 Develop the research objectives
• 2 Design and plan the study
• 3 Write the proposal
• 4 Obtain financial support for the research
• 5 Manage the research
• 6 Draw conclusions and make recommendations
• 7 Write the report
• 8 Disseminate the results
• Part 2 Methods
• Appendix The market for information professionals: A proposal from the Policy Studies Institute

3 - Write the proposal

from Part 1 - The research process

Published online by Cambridge University Press:  09 June 2018

Just as a builder requires a detailed set of plans to guide the building of a house, so a researcher needs a proposal to help structure and manage the research project. Too often, the proposal is regarded as an inconvenience that is only required in order to obtain external funds for a project or to obtain approval for an academic dissertation. It is thought to be something that can be discarded once the funds have been allocated or the approval given. This is a very limited view of research proposals. Those who take it leave themselves without one of the most useful tools for managing research.

Research proposals, in fact, play a number of important rôles in the research process and, while preparing a proposal may seem like a distraction or an unnecessary waste of time, the work involved should ensure that you think through all the aspects concerned with the project before the research itself begins to take over. Because once the project starts rolling it is often too late to begin making changes and adjustments that would have been obvious in advance if the project had been properly prepared.

The purposes of research proposals

Proposals have a number of different purposes. A small in-house project will clearly require a less complicated proposal than a major project for which external funds are being sought. But the purposes they serve will, by and large, be the same.

To gain the approval of a supervisor

The proposal plays an important rôle in justifying the research to a supervisor. It is the vehicle that you use to argue the case for the research, demonstrating that it is important that you are capable of undertaking – and successfully completing – the work, and that the work will enable you to achieve the educational objectives of the exercise.

For academic research projects, you will need to obtain your supervisor's approval for your ideas at an early stage. You will need to be able to show that you have a clear understanding of the general issues and theories associated with the topic that you wish to study. You should be able to cite the key authors in the field and you should be able to demonstrate how your approach fits with the research that others have carried out.

Access options

Save book to kindle.

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle .

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service .

• Write the proposal
• Book: How to Do Research
• Online publication: 09 June 2018
• Chapter DOI: https://doi.org/10.29085/9781856049825.004

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox .

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive .