example of a dissertation analysis

• +44 7897 053596
• [email protected]

Get an experienced writer start working

Review our examples before placing an order, learn how to draft academic papers, a step-by-step guide to dissertation data analysis.

How to Write a Dissertation Conclusion? | Tips & Examples

What is PhD Thesis Writing? | Beginner’s Guide

A data analysis dissertation is a complex and challenging project requiring significant time, effort, and expertise. Fortunately, it is possible to successfully complete a data analysis dissertation with careful planning and execution.

As a student, you must know how important it is to have a strong and well-written dissertation, especially regarding data analysis. Proper data analysis is crucial to the success of your research and can often make or break your dissertation.

To get a better understanding, you may review the data analysis dissertation examples listed below;

• Impact of Leadership Style on the Job Satisfaction of Nurses
• Effect of Brand Love on Consumer Buying Behaviour in Dietary Supplement Sector
• An Insight Into Alternative Dispute Resolution
• An Investigation of Cyberbullying and its Impact on Adolescent Mental Health in UK

3-Step  Dissertation Process!

Get 3+ Topics

Dissertation Proposal

Get Final Dissertation

Types of data analysis for dissertation.

The various types of data Analysis in a Dissertation are as follows;

1.   Qualitative Data Analysis

Qualitative data analysis is a type of data analysis that involves analyzing data that cannot be measured numerically. This data type includes interviews, focus groups, and open-ended surveys. Qualitative data analysis can be used to identify patterns and themes in the data.

2.   Quantitative Data Analysis

Quantitative data analysis is a type of data analysis that involves analyzing data that can be measured numerically. This data type includes test scores, income levels, and crime rates. Quantitative data analysis can be used to test hypotheses and to look for relationships between variables.

3.   Descriptive Data Analysis

Descriptive data analysis is a type of data analysis that involves describing the characteristics of a dataset. This type of data analysis summarizes the main features of a dataset.

4.   Inferential Data Analysis

Inferential data analysis is a type of data analysis that involves making predictions based on a dataset. This type of data analysis can be used to test hypotheses and make predictions about future events.

5.   Exploratory Data Analysis

Exploratory data analysis is a type of data analysis that involves exploring a data set to understand it better. This type of data analysis can identify patterns and relationships in the data.

Time Period to Plan and Complete a Data Analysis Dissertation?

When planning dissertation data analysis, it is important to consider the dissertation methodology structure and time series analysis as they will give you an understanding of how long each stage will take. For example, using a qualitative research method, your data analysis will involve coding and categorizing your data.

This can be time-consuming, so allowing enough time in your schedule is important. Once you have coded and categorized your data, you will need to write up your findings. Again, this can take some time, so factor this into your schedule.

Finally, you will need to proofread and edit your dissertation before submitting it. All told, a data analysis dissertation can take anywhere from several weeks to several months to complete, depending on the project’s complexity. Therefore, starting planning early and allowing enough time in your schedule to complete the task is important.

Essential Strategies for Data Analysis Dissertation

A.   Planning

The first step in any dissertation is planning. You must decide what you want to write about and how you want to structure your argument. This planning will involve deciding what data you want to analyze and what methods you will use for a data analysis dissertation.

B.   Prototyping

Once you have a plan for your dissertation, it’s time to start writing. However, creating a prototype is important before diving head-first into writing your dissertation. A prototype is a rough draft of your argument that allows you to get feedback from your advisor and committee members. This feedback will help you fine-tune your argument before you start writing the final version of your dissertation.

C.   Executing

After you have created a plan and prototype for your data analysis dissertation, it’s time to start writing the final version. This process will involve collecting and analyzing data and writing up your results. You will also need to create a conclusion section that ties everything together.

D.   Presenting

The final step in acing your data analysis dissertation is presenting it to your committee. This presentation should be well-organized and professionally presented. During the presentation, you’ll also need to be ready to respond to questions concerning your dissertation.

Data Analysis Tools

Numerous suggestive tools are employed to assess the data and deduce pertinent findings for the discussion section. The tools used to analyze data and get a scientific conclusion are as follows:

a.     Excel

Excel is a spreadsheet program part of the Microsoft Office productivity software suite. Excel is a powerful tool that can be used for various data analysis tasks, such as creating charts and graphs, performing mathematical calculations, and sorting and filtering data.

b.     Google Sheets

Google Sheets is a free online spreadsheet application that is part of the Google Drive suite of productivity software. Google Sheets is similar to Excel in terms of functionality, but it also has some unique features, such as the ability to collaborate with other users in real-time.

c.     SPSS

SPSS is a statistical analysis software program commonly used in the social sciences. SPSS can be used for various data analysis tasks, such as hypothesis testing, factor analysis, and regression analysis.

d.     STATA

STATA is a statistical analysis software program commonly used in the sciences and economics. STATA can be used for data management, statistical modelling, descriptive statistics analysis, and data visualization tasks.

SAS is a commercial statistical analysis software program used by businesses and organizations worldwide. SAS can be used for predictive modelling, market research, and fraud detection.

R is a free, open-source statistical programming language popular among statisticians and data scientists. R can be used for tasks such as data wrangling, machine learning, and creating complex visualizations.

g.     Python

A variety of applications may be used using the distinctive programming language Python, including web development, scientific computing, and artificial intelligence. Python also has a number of modules and libraries that can be used for data analysis tasks, such as numerical computing, statistical modelling, and data visualization.

Testimonials

Very satisfied students

This is our reason for working. We want to make all students happy, every day. Review us on Sitejabber

Tips to Compose a Successful Data Analysis Dissertation

a.   Choose a Topic You’re Passionate About

The first step to writing a successful data analysis dissertation is to choose a topic you’re passionate about. Not only will this make the research and writing process more enjoyable, but it will also ensure that you produce a high-quality paper.

Choose a topic that is particular enough to be covered in your paper’s scope but not so specific that it will be challenging to obtain enough evidence to substantiate your arguments.

b.   Do Your Research

data analysis in research is an important part of academic writing. Once you’ve selected a topic, it’s time to begin your research. Be sure to consult with your advisor or supervisor frequently during this stage to ensure that you are on the right track. In addition to secondary sources such as books, journal articles, and reports, you should also consider conducting primary research through surveys or interviews. This will give you first-hand insights into your topic that can be invaluable when writing your paper.

c.   Develop a Strong Thesis Statement

After you’ve done your research, it’s time to start developing your thesis statement. It is arguably the most crucial part of your entire paper, so take care to craft a clear and concise statement that encapsulates the main argument of your paper.

Remember that your thesis statement should be arguable—that is, it should be capable of being disputed by someone who disagrees with your point of view. If your thesis statement is not arguable, it will be difficult to write a convincing paper.

d.   Write a Detailed Outline

Once you have developed a strong thesis statement, the next step is to write a detailed outline of your paper. This will offer you a direction to write in and guarantee that your paper makes sense from beginning to end.

Your outline should include an introduction, in which you state your thesis statement; several body paragraphs, each devoted to a different aspect of your argument; and a conclusion, in which you restate your thesis and summarize the main points of your paper.

e.   Write Your First Draft

With your outline in hand, it’s finally time to start writing your first draft. At this stage, don’t worry about perfecting your grammar or making sure every sentence is exactly right—focus on getting all of your ideas down on paper (or onto the screen). Once you have completed your first draft, you can revise it for style and clarity.

And there you have it! Following these simple tips can increase your chances of success when writing your data analysis dissertation. Just remember to start early, give yourself plenty of time to research and revise, and consult with your supervisor frequently throughout the process.

How Does It Work ?

Fill the Form

Writer Starts Working

3+ Topics Emailed!

Studying the above examples gives you valuable insight into the structure and content that should be included in your own data analysis dissertation. You can also learn how to effectively analyze and present your data and make a lasting impact on your readers.

In addition to being a useful resource for completing your dissertation, these examples can also serve as a valuable reference for future academic writing projects. By following these examples and understanding their principles, you can improve your data analysis skills and increase your chances of success in your academic career.

You may also contact Premier Dissertations to develop your data analysis dissertation.

For further assistance, some other resources in the dissertation writing section are shared below;

How Do You Select the Right Data Analysis

How to Write Data Analysis For A Dissertation?

How to Develop a Conceptual Framework in Dissertation?

What is a Hypothesis in a Dissertation?

Get an Immediate Response

Discuss your requirments with our writers

WhatsApp Us Email Us Chat with Us

Get 3+ Free   Dissertation Topics within 24 hours?

Your Number

Academic Level Select Academic Level Undergraduate Masters PhD

Area of Research

admin farhan

Related posts.

Understanding TOK Concepts: A Beginner’s Guide

Research Hypotheses: Directional vs. Non-Directional Hypotheses

Is AP Psychology Hard? Exploring the Challenges and Rewards

Comments are closed.

• Privacy Policy

Buy Me a Coffee

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

Delimitations in Research – Types, Examples and...

Research Design – Types, Methods and Examples

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

Dissertation – Format, Example and Template

Dissertation vs Thesis – Key Differences

Ethical Considerations – Types, Examples and...

Library Guides

Dissertations 2: structure: thematic.

In the humanities, a thematic dissertation is often structured like a long essay. It can contain: 

Title page 

Abstract 

Table of contents 

Introduction  

Literature review (which can be included in the introduction rather than as a separate chapter. Check with your supervisor if you are unsure). 

Theme 1 

Theme 2 

Theme 3 

Conclusion 

Bibliography 

Appendices 

Abstracts are used by other researchers to establish the relevance of the study to their own work. Therefore, they should contain the what, why, who, where and how of your project.  

They are typically between 250 – 300 words long, offer a summary of the main findings and present the conclusions, so you should attempt to write an abstract (if requested), after you have finished writing the dissertation.  

A typical abstract summarises: 

What the study aimed to achieve  

The methodology used 

Why the research was conducted 

Why the research is important 

Who/what was researched 

Table of Contents

The table of contents should list all the items included in your dissertation.  

It is a good idea to use the electronic table of contents feature in Word to automatically link it to your chapter headings and page numbers. Attempting to manually create a table of contents means that you will have to adjust your page numbers every time you edit your work before submission, which may waste valuable time!  

This useful  video will walk you through the formatting of longer documents using the electronic table of contents feature. 

Introduction

The introduction explains the how, what, where, when, why and who of the research. It introduces the reader to your dissertation and should act as a clear guide as to what it will cover.  

The introduction may include the following content: 

Introduce the topic of the dissertation

• State why the topic is of interest 
• Give background information on the subject. 
• Refer to the main debates in the field

Identify the scope of your research 

• Highlight what hasn't already been said by the literature  
• Demonstrate what you seek to investigate, and why 
• Present the aim of the dissertation. 
• Mention your research question or hypothesis 

Indicate your approach  

• Introduce your main argument (especially if you have a research question, rather than hypothesis). 
• Mention your methods/research design. 
• Outline the dissertation structure (introduce the main points that you will discuss in the order they will be presented). 

Normally, the introduction is roughly 10% of a dissertation word count. 

Literature Review

The term “literature” in “literature review” comprises scholarly articles, books, and other sources (e.g. reports) relevant to a particular issue, area of research or theory. In a dissertation, the literature review illustrates what the literature already says on your research subject, providing summary and synthesis of such literature.  

It is generally structured by topic, starting from general background and concepts, and then addressing what can be found - and cannot be found - on the specific focus of your dissertation. Indeed, the literature review should identify gaps in the literature, that your research aims to fill. This requires you to engage critically with the literature, not merely reproduce the critical understanding of others.  

In sum, literature reviews should demonstrate how your research question can be located in a wider field of inquiry. Therefore, a literature review needs to address the connections between your work and the work of others by highlighting links between them. In doing so, you will demonstrate the foundations of your project and show how you are taking the line of inquiry forwards.  

By the end of your literature review, your reader should be able to see: 

The gap in knowledge and understanding which you say exists in the field. 

How your research question will work within that gap. 

The work other researchers have carried out and the issues debated in the field. 

That you have a good understanding of the field and that you are critically engaged with the debates (Burnett, 2009). 

For more detailed guidance on how to write literature reviews, check out the Literature Review Guide. 

Theme Chapters

In a thematic structure, the core chapters present analysis and discussion of different themes relevant to answer the research question and support the overall argument of the dissertation. The chapters will include analysis of texts/ research material. They can explore and connect academic theories/research to develop an argument. Stella Cottrell offers some good guidance on how to structure your theme chapters. Each chapter should have the following elements (Cottrell, 2014, p183):

Theme: What is the theme of this chapter? Sequence your themes logically (e.g. from general to specific).  

Argument: What argument does this chapter present?  

Material: What material you will be using for this chapter? 

Clustering: What are the main points you want to make? Deal with one point at a time, and don't jum around? Dedicate your points to sub-headings and paragraphs.  

Sequence: In what order are you going to present the points you want to make in this chapter? Draw an outline of the chapter before starting writing it.  

Introduction and Conclusion: Each chapter should have a short introduction and conclusion. 

The conclusion is the final chapter of your dissertation. It should flow logically from the previously presented text; therefore, you should avoid introducing new ideas, new data, or a new direction.  

Ideally, the conclusion should leave the reader with a clear understanding of the discovery or argument you have advanced.  

This can be done by: 

Summarising and synthesising your main findings and how they relate to your research question or hypotheses  

Demonstrating the relevance and importance of your work in the wider context of your field. For example, what recommendations would you make for future research? What do we know now that we didn’t know before? 

Link your conclusion to your introduction as both frame your dissertation. 

A conclusion is roughly five to ten percent of the word count of the dissertation. 

Avoid excessive detail. Decide what your reader needs to know. 

Don’t introduce any new information such as theories, data or ideas.  

Sum up the main points of your research.  

Bibliography

While writing your dissertation, you would have referred to the works and research of many different authors and editors in your field of study. These works should be acknowledged in the bibliography where you will list writers alphabetically by surname. 

For example: 

Poloian, L.R. (2013).  Retailing principles: global, multichannel, and managerial viewpoints.  New York: Fairchild.  Biggs, J. and Tang, C. (2011).  Teaching for quality learning at university . Maidenhead: Open University Press.  Ramsay, P., Maier, P. and Price, G. (2010).  Study skills for business and management students . Harlow: Longman. 

Unless otherwise specified by your module leader, the University uses the Harvard (author-date) style of citing and referencing. For more guidance and support on how to reference effectively check out the  Referencing Guide . You can also  book an appointment  with an Academic Engagement Librarian for extra help with referencing. 

While the main results of your study should be placed in the body of your dissertation, any extra information can be placed in the appendices chapter. This supplementary information, for instance, can consist of graphs, charts, or tables that demonstrate less significant results or interview transcripts that would disrupt the flow of the main text if they were included within it.  

You can create one long appendix section or divide it into smaller sections to make it easier to navigate. For example, you might want to have an appendix for images, an appendix for transcripts, and an appendix for graphs. Each appendix (each graph or chart, etc.) should have its own number and title. Further, the sources for all appendices should be acknowledged through referencing and listed in the bibliography. 

Don’t forget to mention each appendix at least once during your dissertation! This can be done using brackets in the following way: (see appendix 1). 

• << Previous: Standard
• Last Updated: Nov 23, 2021 3:47 PM
• URL: https://libguides.westminster.ac.uk/c.php?g=692395

CONNECT WITH US

4 Examples of Academic Writing

#scribendiinc

Written by  Scribendi

The best way to understand what effective academic writing looks like is to review academic writing examples.

Let's begin with four of the most common types of academic writing: research proposals, dissertations, abstracts, and academic articles. We'll be examining each type of writing and providing academic writing samples of each. 

Whether you aim to earn funding for a passion project or are stymied by how to format an abstract, these academic writing examples will help you nail your next undertaking.

Academic Writing Example 1: Research Proposals

A research proposal is an outline of the proposed research of a PhD candidate, a private researcher, or someone hoping to obtain a research grant . 

Your proposal should put your best foot forward: It details your intended research question and how it relates to existing research, makes an argument for why your research should be chosen for advancement or funding, and explains the deliverables you hope to achieve with your research. 

A more detailed look at what proposal writing is and what goes into a research proposal may also be beneficial. Every proposal is different because every project is different. Proposal requirements also differ according to the university or funding agency that reviews the proposal. 

Research Proposal Structure

A cover letter summarizing your proposal and showcasing why you should be chosen

An introduction or abstract

An explanation of the background, purpose, and significance of your research

A research plan or methodology that includes a timeline (a Gantt chart may be beneficial)

A projected budget, if applicable

Academic Writing Sample: Research Proposal Excerpt

Building on the work of the three foundational sociological theorists—Marx, Weber, and Durkheim—and Mark Traugott's theory of the "insurgent barricade," this proposed research will analyze the appearance, use, and disappearance of barricade warfare as an effective battle strategy. 

Focusing on these three theorists, this research will determine which theory or theories best explain the life cycle of barricade warfare, focusing in particular on its disappearance. A brief but comprehensive history of barricade warfare will be provided in addition to the theoretical explanations of barricade warfare's utility.

Research Proposal Writing Tips

Before you format your proposal, contact your targeted university, private organization, or funding agency to confirm what they require for proposals. Then, try to follow this format as closely as possible.

Be detailed when outlining your goals and your funding needs. Connect the objectives of the research to the resources you're requesting.

Be realistic in what you ask for as far as resources—don't ask for more or less than you need, and show evidence to justify your choices.

Don't dedicate too much text in your proposal to describing past research. A summary of key points, arguments, theories, and how your research will build on them should suffice.

Remember that no matter how good your proposal is, it might be rejected. You're likely up against dozens or even hundreds of other candidates who have equally sound proposals. Don't be discouraged if this happens. See it as a learning opportunity for your next proposal.

Academic Writing Example 2: Dissertations

A dissertation is a body of writing that represents original research and is generally written as part of a PhD or master's program. 

Typically, it builds on previous research in the field to make a significant contribution or advancement. You may benefit from more detailed information on what a dissertation is , how to write a dissertation , and how to edit a dissertation .

Dissertation Structure

Introduction/background and the significance of the study

Literature review

Methodology

Results/findings

Conclusion/contribution to the body of research

Academic Writing Sample: Dissertation Excerpt

There are two options for choosing a unit of analysis for this phenomenon: the social artifact (erected barricades) or the social interaction (the collaboration of insurgents engaged in barricade warfare). The best choice is social interaction. 

Most individual occurrences of barricade warfare involve the construction of more than one barricade, and the number of barricades is not necessarily a valid indicator of the sociological magnitude of an insurgence. The most relevant choice is an insurgence, the event of a conflict involving barricade warfare.

Dissertation Writing Tips

Remember to bear in mind the significance of your study. It doesn't have to be paradigm shifting, but you want to infuse the dissertation with reminders of why your research is important.

Don't get bogged down in trying to show that your research is one of a kind or uniquely contributive to the body of research. It likely isn't, and it's more effective to show how you are building on previous research .

Remember to check with your college or university to ensure that you're formatting your dissertation according to the school's expectations.

Ask your advisor questions when you need to.

Be prepared to make alterations to your dissertation according to your thesis committee's suggestions. This doesn't mean you did a bad job—it just means there's room for improvement.

Academic Writing Example 3: Abstracts

The abstract is actually a component of other forms of academic writing, such as scholarly articles and dissertations. The abstract acts as a comprehensive outline of your paper in paragraph form. 

Abstract Structure

Results 

You may want to read more about what abstracts are and why they are important in preparing yourself for writing one.

Academic Writing Sample: Abstract

Barricade warfare has occurred across several spectra, but most notably, it occurred almost exclusively in a 300-year period between the 16th and 19th centuries. Each instance had an inciting incident, but a common thread was the culture of revolution: a revolutionary tradition based on the belief that injustice was being carried out and that, in this case, barricade insurgence was the way to resolve it. 

This study uses the theories of Karl Marx and Emile Durkheim to analyze barricade warfare, its appearance, and its disappearance. Ultimately, neither theory can independently explain this phenomenon. 

Marx offers a reasonable explanation for why barricade warfare may have died, but his theory is difficult to test empirically and fails to explain the absence of recurrences. Conversely, Durkheim's theory is much easier to observe and can explain why barricade warfare has not experienced a renaissance. However, he offered no reason as to why it died in the first place. 

These two theoretical orientations complement each other nicely and, ultimately, neither can stand alone.

Notice that this abstract comes in at under 200 words (a common limit) but nevertheless covers the background of the study, how it was approached, and the results and conclusions of the research. 

If you are struggling to meet a word count, check out 10 Academic Phrases Your Writing Doesn't Need .

Abstract Writing Tips

Be conscious of your word count. Stay under the limit.

Check with your school or target journal to make sure special formatting is not required.

Don't use abbreviations or citations in the abstract.

Don't simply restate your thesis or copy your introduction. Neither of these is an abstract.

Remember that your abstract often gives readers their first impressions of your work. Despite its short length, it deserves a lot of attention. 

Academic Writing Example 4: Articles

Academic articles are pieces of writing intended for publication in academic journals or other scholarly sources. They may be original research studies, literature analyses, critiques , or other forms of scholarly writing.

Article Structure

Abstract and keywords

Introduction

Materials and methods

References and appendices

Academic Writing Sample: Article Excerpt

"Those great revolutionary barricades were places where heroes came together" (Hugo, 2008). This description by Victor Hugo of the 1832 June Rebellion in Paris comes from his seminal work of fiction, Les Miserables. 

Although the account is fictionalized, it is deeply representative of what historian Mark Traugott (2010, p. 225) terms the "culture of revolution." This spirit of heroic response to social injustice swept across Europe during the second half of the millennium and was characterized in part by barricade warfare. 

The phenomenon of the insurgent barricade has essentially disappeared, however, leaving no trace of its short-lived but intense epoch, and the question of why this happened remains a mystery. The theories of Karl Marx and Emile Durkheim, when taken together, provide a compelling explanation for the disappearance of barricade warfare, and the tenets of each theory will be examined to explain this phenomenon.

Article Writing Tips

Follow these detailed steps for writing an article and publishing it in a journal .

Make sure that you follow all of your target journal's guidelines.

Have a second set of educated eyes look over your article to correct typos, confusing language, and unclear arguments.

Don't be discouraged if your article is not chosen for publication. As with proposal writing, you are up against countless others with equally compelling research.

Don't be discouraged if the journal asks you to make changes to your article. This is common. It means they see value in your article, as well as room for improvement.

Whether you're applying for funding, earning an advanced degree, aiming to publish in a journal, or just trying to cram your 4,000-word study into a 150-word abstract, hopefully these academic writing examples have helped get your creative juices flowing. 

Go out there and write! With these academic writing samples at your side, you are sure to model your academic writing appropriately.

Achieve Your Academic Goals

Hire an expert academic editor , or get a free sample, about the author.

Scribendi's in-house editors work with writers from all over the globe to perfect their writing. They know that no piece of writing is complete without a professional edit, and they love to see a good piece of writing transformed into a great one. Scribendi's in-house editors are unrivaled in both experience and education, having collectively edited millions of words and obtained numerous degrees. They love consuming caffeinated beverages, reading books of various genres, and relaxing in quiet, dimly lit spaces.

Have You Read?

"The Complete Beginner's Guide to Academic Writing"

Related Posts

10 Academic Phrases Your Writing Doesn't Need

21 Legit Research Databases for Free Journal Articles in 2022

Grant Writing Basics

Upload your file(s) so we can calculate your word count, or enter your word count manually.

We will also recommend a service based on the file(s) you upload.

English is not my first language. I need English editing and proofreading so that I sound like a native speaker.

I need to have my journal article, dissertation, or term paper edited and proofread, or I need help with an admissions essay or proposal.

I have a novel, manuscript, play, or ebook. I need editing, copy editing, proofreading, a critique of my work, or a query package.

I need editing and proofreading for my white papers, reports, manuals, press releases, marketing materials, and other business documents.

I need to have my essay, project, assignment, or term paper edited and proofread.

I want to sound professional and to get hired. I have a resume, letter, email, or personal document that I need to have edited and proofread.

 Prices include your personal % discount.

 Prices include % sales tax ( ).

How To Write A Research Proposal

A Straightforward How-To Guide (With Examples)

By: Derek Jansen (MBA) | Reviewed By: Dr. Eunice Rautenbach | August 2019 (Updated April 2023)

Writing up a strong research proposal for a dissertation or thesis is much like a marriage proposal. It’s a task that calls on you to win somebody over and persuade them that what you’re planning is a great idea. An idea they’re happy to say ‘yes’ to. This means that your dissertation proposal needs to be   persuasive ,   attractive   and well-planned. In this post, I’ll show you how to write a winning dissertation proposal, from scratch.

Before you start:

– Understand exactly what a research proposal is – Ask yourself these 4 questions

The 5 essential ingredients:

• The title/topic
• The introduction chapter
• The scope/delimitations
• Preliminary literature review
• Design/ methodology
• Practical considerations and risks 

What Is A Research Proposal?

The research proposal is literally that: a written document that communicates what you propose to research, in a concise format. It’s where you put all that stuff that’s spinning around in your head down on to paper, in a logical, convincing fashion.

Convincing   is the keyword here, as your research proposal needs to convince the assessor that your research is   clearly articulated   (i.e., a clear research question) ,   worth doing   (i.e., is unique and valuable enough to justify the effort), and   doable   within the restrictions you’ll face (time limits, budget, skill limits, etc.). If your proposal does not address these three criteria, your research won’t be approved, no matter how “exciting” the research idea might be.

PS – if you’re completely new to proposal writing, we’ve got a detailed walkthrough video covering two successful research proposals here . 

How do I know I’m ready?

Before starting the writing process, you need to   ask yourself 4 important questions .  If you can’t answer them succinctly and confidently, you’re not ready – you need to go back and think more deeply about your dissertation topic .

You should be able to answer the following 4 questions before starting your dissertation or thesis research proposal:

• WHAT is my main research question? (the topic)
• WHO cares and why is this important? (the justification)
• WHAT data would I need to answer this question, and how will I analyse it? (the research design)
• HOW will I manage the completion of this research, within the given timelines? (project and risk management)

If you can’t answer these questions clearly and concisely,   you’re not yet ready   to write your research proposal – revisit our   post on choosing a topic .

If you can, that’s great – it’s time to start writing up your dissertation proposal. Next, I’ll discuss what needs to go into your research proposal, and how to structure it all into an intuitive, convincing document with a linear narrative.

The 5 Essential Ingredients

Research proposals can vary in style between institutions and disciplines, but here I’ll share with you a   handy 5-section structure   you can use. These 5 sections directly address the core questions we spoke about earlier, ensuring that you present a convincing proposal. If your institution already provides a proposal template, there will likely be substantial overlap with this, so you’ll still get value from reading on.

For each section discussed below, make sure you use headers and sub-headers (ideally, numbered headers) to help the reader navigate through your document, and to support them when they need to revisit a previous section. Don’t just present an endless wall of text, paragraph after paragraph after paragraph…

Top Tip:   Use MS Word Styles to format headings. This will allow you to be clear about whether a sub-heading is level 2, 3, or 4. Additionally, you can view your document in ‘outline view’ which will show you only your headings. This makes it much easier to check your structure, shift things around and make decisions about where a section needs to sit. You can also generate a 100% accurate table of contents using Word’s automatic functionality.

Ingredient #1 – Topic/Title Header

Your research proposal’s title should be your main research question in its simplest form, possibly with a sub-heading providing basic details on the specifics of the study. For example:

“Compliance with equality legislation in the charity sector: a study of the ‘reasonable adjustments’ made in three London care homes”

As you can see, this title provides a clear indication of what the research is about, in broad terms. It paints a high-level picture for the first-time reader, which gives them a taste of what to expect.   Always aim for a clear, concise title . Don’t feel the need to capture every detail of your research in your title – your proposal will fill in the gaps.

Need a helping hand?

Ingredient #2 – Introduction

In this section of your research proposal, you’ll expand on what you’ve communicated in the title, by providing a few paragraphs which offer more detail about your research topic. Importantly, the focus here is the   topic   – what will you research and why is that worth researching? This is not the place to discuss methodology, practicalities, etc. – you’ll do that later.

You should cover the following:

• An overview of the   broad area   you’ll be researching – introduce the reader to key concepts and language
• An explanation of the   specific (narrower) area   you’ll be focusing, and why you’ll be focusing there
• Your research   aims   and   objectives
• Your   research question (s) and sub-questions (if applicable)

Importantly, you should aim to use short sentences and plain language – don’t babble on with extensive jargon, acronyms and complex language. Assume that the reader is an intelligent layman – not a subject area specialist (even if they are). Remember that the   best writing is writing that can be easily understood   and digested. Keep it simple.

Note that some universities may want some extra bits and pieces in your introduction section. For example, personal development objectives, a structural outline, etc. Check your brief to see if there are any other details they expect in your proposal, and make sure you find a place for these.

Ingredient #3 – Scope

Next, you’ll need to specify what the scope of your research will be – this is also known as the delimitations . In other words, you need to make it clear what you will be covering and, more importantly, what you won’t be covering in your research. Simply put, this is about ring fencing your research topic so that you have a laser-sharp focus.

All too often, students feel the need to go broad and try to address as many issues as possible, in the interest of producing comprehensive research. Whilst this is admirable, it’s a mistake. By tightly refining your scope, you’ll enable yourself to   go deep   with your research, which is what you need to earn good marks. If your scope is too broad, you’re likely going to land up with superficial research (which won’t earn marks), so don’t be afraid to narrow things down.

Ingredient #4 – Literature Review

In this section of your research proposal, you need to provide a (relatively) brief discussion of the existing literature. Naturally, this will not be as comprehensive as the literature review in your actual dissertation, but it will lay the foundation for that. In fact, if you put in the effort at this stage, you’ll make your life a lot easier when it’s time to write your actual literature review chapter.

There are a few things you need to achieve in this section:

• Demonstrate that you’ve done your reading and are   familiar with the current state of the research   in your topic area.
• Show that   there’s a clear gap   for your specific research – i.e., show that your topic is sufficiently unique and will add value to the existing research.
• Show how the existing research has shaped your thinking regarding   research design . For example, you might use scales or questionnaires from previous studies.

When you write up your literature review, keep these three objectives front of mind, especially number two (revealing the gap in the literature), so that your literature review has a   clear purpose and direction . Everything you write should be contributing towards one (or more) of these objectives in some way. If it doesn’t, you need to ask yourself whether it’s truly needed.

Top Tip:  Don’t fall into the trap of just describing the main pieces of literature, for example, “A says this, B says that, C also says that…” and so on. Merely describing the literature provides no value. Instead, you need to   synthesise   it, and use it to address the three objectives above.

Ingredient #5 – Research Methodology

Now that you’ve clearly explained both your intended research topic (in the introduction) and the existing research it will draw on (in the literature review section), it’s time to get practical and explain exactly how you’ll be carrying out your own research. In other words, your research methodology.

In this section, you’ll need to   answer two critical questions :

• How   will you design your research? I.e., what research methodology will you adopt, what will your sample be, how will you collect data, etc.
• Why   have you chosen this design? I.e., why does this approach suit your specific research aims, objectives and questions?

In other words, this is not just about explaining WHAT you’ll be doing, it’s also about explaining WHY. In fact, the   justification is the most important part , because that justification is how you demonstrate a good understanding of research design (which is what assessors want to see).

Some essential design choices you need to cover in your research proposal include:

• Your intended research philosophy (e.g., positivism, interpretivism or pragmatism )
• What methodological approach you’ll be taking (e.g., qualitative , quantitative or mixed )
• The details of your sample (e.g., sample size, who they are, who they represent, etc.)
• What data you plan to collect (i.e. data about what, in what form?)
• How you plan to collect it (e.g., surveys , interviews , focus groups, etc.)
• How you plan to analyse it (e.g., regression analysis, thematic analysis , etc.)
• Ethical adherence (i.e., does this research satisfy all ethical requirements of your institution, or does it need further approval?)

This list is not exhaustive – these are just some core attributes of research design. Check with your institution what level of detail they expect. The “ research onion ” by Saunders et al (2009) provides a good summary of the various design choices you ultimately need to make – you can   read more about that here .

Don’t forget the practicalities…

In addition to the technical aspects, you will need to address the   practical   side of the project. In other words, you need to explain   what resources you’ll need   (e.g., time, money, access to equipment or software, etc.) and how you intend to secure these resources. You need to show that your project is feasible, so any “make or break” type resources need to already be secured. The success or failure of your project cannot depend on some resource which you’re not yet sure you have access to.

Another part of the practicalities discussion is   project and risk management . In other words, you need to show that you have a clear project plan to tackle your research with. Some key questions to address:

• What are the timelines for each phase of your project?
• Are the time allocations reasonable?
• What happens if something takes longer than anticipated (risk management)?
• What happens if you don’t get the response rate you expect?

A good way to demonstrate that you’ve thought this through is to include a Gantt chart and a risk register (in the appendix if word count is a problem). With these two tools, you can show that you’ve got a clear, feasible plan, and you’ve thought about and accounted for the potential risks.

Tip – Be honest about the potential difficulties – but show that you are anticipating solutions and workarounds. This is much more impressive to an assessor than an unrealistically optimistic proposal which does not anticipate any challenges whatsoever.

Final Touches: Read And Simplify

The final step is to edit and proofread your proposal – very carefully. It sounds obvious, but all too often poor editing and proofreading ruin a good proposal. Nothing is more off-putting for an assessor than a poorly edited, typo-strewn document. It sends the message that you either do not pay attention to detail, or just don’t care. Neither of these are good messages. Put the effort into editing and proofreading your proposal (or pay someone to do it for you) – it will pay dividends.

When you’re editing, watch out for ‘academese’. Many students can speak simply, passionately and clearly about their dissertation topic – but become incomprehensible the moment they turn the laptop on. You are not required to write in any kind of special, formal, complex language when you write academic work. Sure, there may be technical terms, jargon specific to your discipline, shorthand terms and so on. But, apart from those,   keep your written language very close to natural spoken language   – just as you would speak in the classroom. Imagine that you are explaining your project plans to your classmates or a family member. Remember, write for the intelligent layman, not the subject matter experts. Plain-language, concise writing is what wins hearts and minds – and marks!

Let’s Recap: Research Proposal 101

And there you have it – how to write your dissertation or thesis research proposal, from the title page to the final proof. Here’s a quick recap of the key takeaways:

• The purpose of the research proposal is to   convince   – therefore, you need to make a clear, concise argument of why your research is both worth doing and doable.
• Make sure you can ask the critical what, who, and how questions of your research   before   you put pen to paper.
• Title – provides the first taste of your research, in broad terms
• Introduction – explains what you’ll be researching in more detail
• Scope – explains the boundaries of your research
• Literature review – explains how your research fits into the existing research and why it’s unique and valuable
• Research methodology – explains and justifies how you will carry out your own research

Hopefully, this post has helped you better understand how to write up a winning research proposal. If you enjoyed it, be sure to check out the rest of the Grad Coach Blog . If your university doesn’t provide any template for your proposal, you might want to try out our free research proposal template .

Psst… there’s more!

This post is an extract from our bestselling Udemy Course, Research Proposal Bootcamp . If you want to work smart, you don't want to miss this .

You Might Also Like:

29 Comments

Thank you so much for the valuable insight that you have given, especially on the research proposal. That is what I have managed to cover. I still need to go back to the other parts as I got disturbed while still listening to Derek’s audio on you-tube. I am inspired. I will definitely continue with Grad-coach guidance on You-tube.

Thanks for the kind words :). All the best with your proposal.

First of all, thanks a lot for making such a wonderful presentation. The video was really useful and gave me a very clear insight of how a research proposal has to be written. I shall try implementing these ideas in my RP.

Once again, I thank you for this content.

I found reading your outline on writing research proposal very beneficial. I wish there was a way of submitting my draft proposal to you guys for critiquing before I submit to the institution.

Hi Bonginkosi

Thank you for the kind words. Yes, we do provide a review service. The best starting point is to have a chat with one of our coaches here: https://gradcoach.com/book/new/ .

Hello team GRADCOACH, may God bless you so much. I was totally green in research. Am so happy for your free superb tutorials and resources. Once again thank you so much Derek and his team.

You’re welcome, Erick. Good luck with your research proposal 🙂

thank you for the information. its precise and on point.

Really a remarkable piece of writing and great source of guidance for the researchers. GOD BLESS YOU for your guidance. Regards

Thanks so much for your guidance. It is easy and comprehensive the way you explain the steps for a winning research proposal.

Thank you guys so much for the rich post. I enjoyed and learn from every word in it. My problem now is how to get into your platform wherein I can always seek help on things related to my research work ? Secondly, I wish to find out if there is a way I can send my tentative proposal to you guys for examination before I take to my supervisor Once again thanks very much for the insights

Thanks for your kind words, Desire.

If you are based in a country where Grad Coach’s paid services are available, you can book a consultation by clicking the “Book” button in the top right.

Best of luck with your studies.

May God bless you team for the wonderful work you are doing,

If I have a topic, Can I submit it to you so that you can draft a proposal for me?? As I am expecting to go for masters degree in the near future.

Thanks for your comment. We definitely cannot draft a proposal for you, as that would constitute academic misconduct. The proposal needs to be your own work. We can coach you through the process, but it needs to be your own work and your own writing.

Best of luck with your research!

I found a lot of many essential concepts from your material. it is real a road map to write a research proposal. so thanks a lot. If there is any update material on your hand on MBA please forward to me.

GradCoach is a professional website that presents support and helps for MBA student like me through the useful online information on the page and with my 1-on-1 online coaching with the amazing and professional PhD Kerryen.

Thank you Kerryen so much for the support and help 🙂

I really recommend dealing with such a reliable services provider like Gradcoah and a coach like Kerryen.

Hi, Am happy for your service and effort to help students and researchers, Please, i have been given an assignment on research for strategic development, the task one is to formulate a research proposal to support the strategic development of a business area, my issue here is how to go about it, especially the topic or title and introduction. Please, i would like to know if you could help me and how much is the charge.

This content is practical, valuable, and just great!

Thank you very much!

Hi Derek, Thank you for the valuable presentation. It is very helpful especially for beginners like me. I am just starting my PhD.

This is quite instructive and research proposal made simple. Can I have a research proposal template?

Great! Thanks for rescuing me, because I had no former knowledge in this topic. But with this piece of information, I am now secured. Thank you once more.

I enjoyed listening to your video on how to write a proposal. I think I will be able to write a winning proposal with your advice. I wish you were to be my supervisor.

Dear Derek Jansen,

Thank you for your great content. I couldn’t learn these topics in MBA, but now I learned from GradCoach. Really appreciate your efforts….

From Afghanistan!

I have got very essential inputs for startup of my dissertation proposal. Well organized properly communicated with video presentation. Thank you for the presentation.

Wow, this is absolutely amazing guys. Thank you so much for the fruitful presentation, you’ve made my research much easier.

this helps me a lot. thank you all so much for impacting in us. may god richly bless you all

How I wish I’d learn about Grad Coach earlier. I’ve been stumbling around writing and rewriting! Now I have concise clear directions on how to put this thing together. Thank you!

Fantastic!! Thank You for this very concise yet comprehensive guidance.

Even if I am poor in English I would like to thank you very much.

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

Goldman Sachs: Time To Take Some Profit (Technical Analysis)

• Goldman Sachs stock has seen significant price appreciation since my last BUY thesis, outperforming the S&P 500 by also twofold.
• However, the heightened valuation risks and potential profitability pressure are weakening the BUY thesis.
• My specific profit concerns include uncertain macroeconomic conditions and operation costs escalation.
• This idea was discussed in more depth with members of my private investing community, Envision Early Retirement. Learn More »

Michael M. Santiago

My last article , published in Oct. 2023, argued for a BUY thesis on Goldman Sachs Group ( NYSE: GS ) when it was trading near its tangible book value at that time. As argued in our article:

Buying good banks such as GS at (or near) their tangible book value ("TBV") is a no-brainer for us. It's a deal where we are only paying for the hard assets (those that can be easily valued and liquidated) and getting everything else for free - such as its future earnings, brand name, customer relationships, et al.

As seen in the chart below, the stock has indeed delivered market-beating returns since then. To wit, GS enjoyed a price appreciation of more than 39% and a total return close to 42%, almost doubling the S&P 500's return in the same period.

Seeking Alpha

However, such a sizable price rally has weakened the BUY thesis because of the heightened valuation risks. The chart below shows the GS' price-to-tangible book value ratio in the past few years. As seen, the stock traded below TBV a couple of times (and the Oct. 2023 time frame was one of them). Currently, the P/TBV ratio is 1.379x, not only far above my ideal entry point of 1x but also above its historical average of 1.146x by a good margin.

Next, I will analyze some of the other concerns that have developed since my last writing.

Profitability pressure

Besides the heightened valuation risks just mentioned, I also anticipate some profitability pressure in the near future. Other analysts seem to share the same view as reflected in the chart below. As seen, in the past 90 days, a total of 15 analysts revised the next quarter's EPS forecast downward and only 2 revised it upward.

The top concerns on my mind are uncertain macroeconomic conditions and operation costs. Inflation remains stubbornly elevated, and as a result, there is no definitive direction or timeframe for interest rate changes in my view. Sure enough, if interest rates (and inflation) stay elevated, it could buoy GS fixed income business. Nevertheless, high rates mostly like would cause a slowdown in some capital market activity and negatively impact GS's other segments. Also, if inflation persists, I anticipate operating costs, mostly compensation and benefits expenses, to further increase. And such increases would weigh on its bottom line. I think the bottom has already been feeling such pressure recently as reflected in the data provided below.

To wit, the chart shows GS's profit margin (top panel) and its ROE, return on equity (bottom panel), compared to its historical average in the past few years. As seen, GS's profit margin has recently slipped from its peak substantially. Its profit margin currently hovers around 18.41%, not only far below its recent peak level of around 34% but also far below its historical average of 26.52% by a good gap. The bottom panel paints the same picture in terms of its ROE. Despite the help of higher interest income due to elevated rates, its current ROE of 7.27% is only about 1/3 of its recent peak of around 21% and also below its historical average of 11.95% by a large margin.

Other risks and final thoughts

Besides the above valuation and fundamental factors, its technical trading pattern also sends mixed signals to me. The next chart shows its trading pattern in the past 6 months. Combined with the fundamental analysis above, I think GS could be trading in a sideways consolidation window of around $400 for the next few months to come. On the positive side, the stock recently broke out the $400 resistance level (also happens to be about the 20-day moving average) and has stayed there thus far. However, now how little trading volume has occurred in this price range (shown by the horizontal volume bars on the chart). Such low volume indicates a lack of conviction from both new buyers at this new price level in my interpretation. In contrast, the vast majority of volume for recent trading occurred in the $380 to $390 range (as shown by the two longest horizon bars). The stock would have a difficult time finding a definitive upward momentum until investors in this range are replaced by more enthusiastic ones.

Source: StockCharts.com

I want to be crystal clear that I am not arguing for a bearish thesis on GS. It is a strong investment bank in my view and there are plenty of positives going on also, especially in the long term. It is the leader in M&A activity and equity underwriting in my view. And I have no doubt that it is best poised to benefit if/when the capital markets begin to show signs of pickup. Management has also been making some key strategic improvements to position its growth in the future. For example, the company has been streamlining its consumer businesses, divesting its non-core GreenSky portfolio, and completing the selling of essentially all of its Marcus personal loan portfolio in 2023. These efforts should help to better focus the bank on its core business, help to control costs, and also bolster margins in the future.

To conclude, the goal of this article is to downgrade my rating on GS from BUY to HOLD. To reiterate, I am NOT trying to argue that GS is a bad bank. To the opposite, my view is that it offers compelling long-term growth catalysts with its strong brand recognition, talent pool, and focus on high-margin investment banking activities. My downgrade is mainly motivated by near-term risk/reward analysis. The current valuation appears stretched compared to historical averages and I see a few signs of profitability pressure. Additionally, weak technical indicators suggest a sideways consolidation window in the near term. Given these considerations, I do not think GS would be able to provide the level of returns it did in the past few months.

As you can tell, our core style is to provide actionable and unambiguous ideas from our independent research. If your share this investment style, check out Envision Early Retirement. It provides at least 1x in-depth articles per week on such ideas.

We have helped our members not only to beat S&P 500 but also avoid heavy drawdowns despite the extreme volatilities in BOTH the equity AND bond market.

Join for a 100% Risk-Free trial and see if our proven method can help you too.

This article was written by

Envision Research, aka Lucas Ma, has over 15+ years of investment experience and holds a Masters with in Quantitative Investment and a PhD in Mechanical Engineering with a focus on renewable energy, both from Stanford University. He also has 30+ years of hands-on experience in high-tech R&D and consulting, housing sector, credit sector, and actual portfolio management.

He leads the investing group Envision Early Retirement along with Sensor Unlimited where they offer proven solutions to generate both high income and high growth with isolated risks through dynamic asset allocation. Features include: two model portfolios - one for short-term survival/withdrawal and one for aggressive long-term growth, direct access via chat to discuss ideas, monthly updates on all holdings, tax discussions, and ticker critiques by request.

Analyst’s Disclosure: I/we have no stock, option or similar derivative position in any of the companies mentioned, and no plans to initiate any such positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Seeking Alpha's Disclosure: Past performance is no guarantee of future results. No recommendation or advice is being given as to whether any investment is suitable for a particular investor. Any views or opinions expressed above may not reflect those of Seeking Alpha as a whole. Seeking Alpha is not a licensed securities dealer, broker or US investment adviser or investment bank. Our analysts are third party authors that include both professional investors and individual investors who may not be licensed or certified by any institute or regulatory body.

Recommended For You

About gs stock, related stocks, trending analysis, trending news.

• Blogs by Topic

The GoLand Blog

A cross-platform Go IDE with extended support for JavaScript, TypeScript, and databases

• Twitter Twitter
• Youtube Youtube
• slack slack

Data Flow Analysis for Go 

GoLand 2023.3 comes with support for data flow analysis (DFA). In this post, we’ll introduce the feature, explain how it works, and show some real-world examples of how DFA can detect bugs on the fly!

Thanks to the CLion team for helping us by porting their powerful DFA engine. For now, the GoLand engine only implements a limited number of DFA features, but more will be added in subsequent releases. The CLion team has also covered a variety of other topics, including a deeper dive into implementation specifics, on their blog .

What is data flow analysis?

DFA is a type of static code analysis that analyzes how data flows through a program. In basic terms, it calculates the possible values of variables at different points in the program’s execution. With this information, you can find various potential bugs, such as nil dereferences, endless loops, constant conditions, and other incorrect or atypical program behavior.

Let’s look at a straightforward example of DFA in action in the form of a simple function:

A common way to perform DFA starts with building a control flow graph (CFG) of the analyzed function. The CFG of this dummy function is provided below. For clarity, all statements (lines of code) are numbered according to their corresponding code snippet.

You can think about CFG as a simple graph that reflects the function’s execution. The graph nodes correspond to code blocks, and the edges reflect conditional and unconditional jumps between them. You don’t need to know the exact formal definition of a CFG or how to build them for this article, but if you’d like to learn about CFGs, you can visit this link .

Once the CFG has been built, the main stage of the analysis can begin. During this stage, the DFA computes all of the possible values of variables that can follow each function statement. Roughly speaking, this can be done by propagating values through statements (such as assignments) and the edges of the CFG, taking into account the reachability of the CFG’s nodes.

For example, the possible value set of the variable r after statement 9 is {nil, new(Resource)} . The nil value is obtained from statement 1 by propagating it through the path 1 -> 2 -> 4 -> 9. The new(Resource) value is obtained by propagating it through the path 1 -> 2 -> 4 -> 5 -> 6 -> 9, taking into account assignments on lines 5 and 9.

We can use the information obtained about variable values to find potential bugs in the corresponding programs. For example, since we know that, after statement 9, the variable r can be nil , that means there can be a nil dereference on line 10.

Challenges of data flow analysis

As an introduction to the potential pitfalls and difficulties associated with implementing data flow analysis, let’s take a look at a slightly modified version of our previous example function:

The corresponding CFG looks like this:

DFA, like other static analysis tools, over-approximates the behavior of programs. In our case, this means that DFA computes the upper bound of possible variable values. In this example, data flow analysis infers that the possible value set of the variable init in statement 10 is {false, true} . Hence, both the branches of the condition on line 10 are reachable, which means an execution can reach statement 11. In statement 11, the value set of variable r is {nil, new(Resource)} . Thus, we can infer that there is a potential nil dereference on line 11. 

But that’s not really true. In fact, the variable init can take both true and false values at statement 10. However, the reachability of the condition init == true also depends on the condition initializeResource == true . If the latter is met, then init can only take the value true, and if it isn’t met, then init can only be false. To identify such cases, we must use contexts. Let’s assume that we’re analyzing a function in two different contexts. The first context corresponds to a case where initializeResource is true , the second one corresponds to a case where initializeResource is false . These contexts are most easily described as a clone of the CFG:

As you can see, there are two different contexts (surrounded by a dashed border). In each context, we can analyze statements 9, 10, and 11 in different ways. For example, in statement 10 of the context initializeResource == true , the variable init can only take a true value, and variable r can only take a new(Resource) value. Therefore, in this context, statement 11 is reachable, but a nil dereference isn’t possible. In statement 10 of the context initializeResource == false , variable r can take a nil value. Since the value of init can only be false , statement 11 is not reachable in this context and therefore a nil dereference isn’t possible. As such, a nil dereference cannot occur in either context.

Using contexts in static analysis allows us to improve the quality of the analysis and weed out false-positives. To support this, exit statements of the if statement are split into two different contexts, duplicating the subsequent nodes of the control flow graph and analyzing them independently to identify all the possible data paths.

The capabilities of data flow analysis in GoLand

Constant conditions detection. Constant conditions represent a crucial type of data flow inspection. The constant condition inspection uses the DFA execution data to determine if certain conditions are constant. Here are two examples:

Example 1: In this example, DFA has deduced that the condition err != nil is always false . To show that this is indeed the case, let’s consider what values the err variable can take in the condition on line 191. There are two main cases – when allF is true and when allF is false after the for loop is executed. If allF is true after the for loop is executed, then err will be nil on line 191, otherwise there will be a return from the function on line 186. The remaining eventuality, when allF is false after the for loop is executed, can only happen if line 177 is reachable. After line 177 is executed, we can be sure of two things: firstly, that err is nil (otherwise the execution of the loop would have continued on line 175), and secondly, that the execution of the loop has been interrupted, and therefore the variable err won’t be assigned any other value. Hence, in cases where allF is false , the variable err can only ever be nil . Thus, the condition err != nil is always false . 

Example 2: Here is a simpler example in which DFA deduces that the condition r0k != nil on line 193 is always true . This happens because the implicit dereference r0k.License is present on line 191, after which the variable r0k cannot be nil . Although the derived constant condition inspection does not accurately show a real problem in the code, it reveals strange behavior in the program. In fact, issues could become apparent at runtime after the potential nil dereference of the variable r0k on line 191, as the author of the code implies that r0k can be nil .

These examples show how the constant condition inspection can allow you to identify peculiar points or strange behavior in the program’s code.

Potential nil dereference. DFA can detect a nil dereference for a variable even in code that seems absolutely normal to the naked eye. Let’s see how this is possible:

Example 3: In this example, DFA infers that there can be a nil dereference of the variable conf on line 273. This may seem strange because the code takes into account cases where the variable conf is nil . In such a case, there should be a return from the function on line 269, and so dereference of the conf variable shouldn’t be reachable. However, there are actually two different conf variables. The first one is declared on line 249 and the second on line 261. Thus, the last declaration shadows the previous one.

This can lead to a nil dereference. Let’s assume that the first conf variable (line 249) is nil but the second conf variable (line 261) is not nil , and let’s also assume that the corresponding error variable is nil . In this case, there is no return from the function on lines 262 and 269, which means we reach the conf dereference on line 273. This dereference corresponds to the first conf variable and causes issues at runtime. For this reason, we should be careful with nested short variable declarations!

Example 4 : DFA deduces a potential nil dereference of the variable pod on line 260. This function takes into account the nilablility of the variable pod (there is a condition pod != nil on line 254), so the author of the code implies that the variable pod can be nil within the if statement. But in this case, there will be a nil dereference on line 260.

Error may be not nil . This inspection reports cases in which variables might have nil or an unexpected value because of the associated error that is not checked for being non-nil .

The analysis is currently intra-procedural and does not consider user-imposed contracts on the function. Therefore, in specific situations, there may be false positives. For cases such as these, you can use a quick-fix to ask the DFA not to analyze or report these errors.

In the example provided, the variable file could either have the value nil or an unexpected value if err is not nil.

Try DFA for yourself!

You can try out these improvements now in the GoLand 2024.1 Release Candidate or wait for the 2024.1 version . It’s also available for 2023.3 users in early access, but is disabled by default. To enable it, go to Settings | Editor | Inspections | Go | Data Flow Analysis (experimental) . 

Subscribe to GoLang Blog updates

By submitting this form, I agree that JetBrains s.r.o. ("JetBrains") may use my name, email address, and location data to send me newsletters, including commercial communications, and to process my personal data for this purpose. I agree that JetBrains may process said data using third-party services for this purpose in accordance with the JetBrains Privacy Policy . I understand that I can revoke this consent at any time in my profile . In addition, an unsubscribe link is included in each email.

Thanks, we've got you!

Discover more

Goland 2024.1 Beta Is Out!

Get the Beta build via the Toolbox App, from our website, by using a snap package (for Ubuntu), or right from inside GoLand by selecting Check IDE updates for: Early Access Program in Settings | Appearance & Behavior | System Settings | Updates. Download GoLand 2024.1 Beta…

GoLand 2024.1: EAP Program and Roadmap

The Early Access Program for GoLand 2024.1 is now open! In this post, we’ll share our plans for the upcoming release and what has been done already in the first EAP build.

GoLand 2023.3 Is Available!

GoLand 2023.3 is out! It introduces full support for AI Assistant, early access for dev containers integration, as well as multiple Go-specific hints, refactorings, and quick-fixes to improve your productivity!

Goland 2023.3 Beta Is Out!

Get the Beta build via the Toolbox App, from our website, by using a snap package (for Ubuntu), or right from inside GoLand by selecting Check IDE updates for: Early Access Program in Settings | Appearance & Behavior | System Settings | Updates. Download GoLand Beta …