analysis chapter in thesis

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Dissertations 5: findings, analysis and discussion: home.

• Results/Findings

Alternative Structures

The time has come to show and discuss the findings of your research. How to structure this part of your dissertation? 

Dissertations can have different structures, as you can see in the dissertation  structure  guide.

Dissertations organised by sections

Many dissertations are organised by sections. In this case, we suggest three options. Note that, if within your course you have been instructed to use a specific structure, you should do that. Also note that sometimes there is considerable freedom on the structure, so you can come up with other structures too. 

A) More common for scientific dissertations and quantitative methods:

- Results chapter 

- Discussion chapter

Example: 

• Introduction
• Literature review
• Methodology
• (Recommendations)

if you write a scientific dissertation, or anyway using quantitative methods, you will have some  objective  results that you will present in the Results chapter. You will then interpret the results in the Discussion chapter.  

B) More common for qualitative methods

- Analysis chapter. This can have more descriptive/thematic subheadings.

- Discussion chapter. This can have more descriptive/thematic subheadings.

• Case study of Company X (fashion brand) environmental strategies 
• Successful elements
• Lessons learnt
• Criticisms of Company X environmental strategies 
• Possible alternatives

C) More common for qualitative methods

- Analysis and discussion chapter. This can have more descriptive/thematic titles.

• Case study of Company X (fashion brand) environmental strategies 

If your dissertation uses qualitative methods, it is harder to identify and report objective data. Instead, it may be more productive and meaningful to present the findings in the same sections where you also analyse, and possibly discuss, them. You will probably have different sections dealing with different themes. The different themes can be subheadings of the Analysis and Discussion (together or separate) chapter(s). 

Thematic dissertations

If the structure of your dissertation is thematic ,  you will have several chapters analysing and discussing the issues raised by your research. The chapters will have descriptive/thematic titles. 

• Background on the conflict in Yemen (2004-present day)
• Classification of the conflict in international law  
• International law violations
• Options for enforcement of international law
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• Last Updated: Aug 4, 2023 2:17 PM
• URL: https://libguides.westminster.ac.uk/c.php?g=696975

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Writing the Data Analysis Chapter(s): Results and Evidence

Posted by Rene Tetzner | Oct 19, 2021 | PhD Success | 0 |

4.4 Writing the Data Analysis Chapter(s): Results and Evidence

Unlike the introduction, literature review and methodology chapter(s), your results chapter(s) will need to be written for the first time as you draft your thesis even if you submitted a proposal, though this part of your thesis will certainly build upon the preceding chapters. You should have carefully recorded and collected the data (test results, participant responses, computer print outs, observations, transcriptions, notes of various kinds etc.) from your research as you conducted it, so now is the time to review, organise and analyse the data. If your study is quantitative in nature, make sure that you know what all the numbers mean and that you consider them in direct relation to the topic, problem or phenomenon you are investigating, and especially in relation to your research questions and hypotheses. You may find that you require the services of a statistician to help make sense of the data, in which case, obtaining that help sooner rather than later is advisable, because you need to understand your results thoroughly before you can write about them. If, on the other hand, your study is qualitative, you will need to read through the data you have collected several times to become familiar with them both as a whole and in detail so that you can establish important themes, patterns and categories. Remember that ‘qualitative analysis is a creative process and requires thoughtful judgments about what is significant and meaningful in the data’ (Roberts, 2010, p.174; see also Miles & Huberman, 1994) – judgements that often need to be made before the findings can be effectively analysed and presented. If you are combining methodologies in your research, you will also need to consider relationships between the results obtained from the different methods, integrating all the data you have obtained and discovering how the results of one approach support or correlate with the results of another. Ideally, you will have taken careful notes recording your initial thoughts and analyses about the sources you consulted and the results and evidence provided by particular methods and instruments as you put them into practice (as suggested in Sections 2.1.2 and 2.1.4), as these will prove helpful while you consider how best to present your results in your thesis.

Although the ways in which to present and organise the results of doctoral research differ markedly depending on the nature of the study and its findings, as on author and committee preferences and university and department guidelines, there are several basic principles that apply to virtually all theses. First and foremost is the need to present the results of your research both clearly and concisely, and in as objective and factual a manner as possible. There will be time and space to elaborate and interpret your results and speculate on their significance and implications in the final discussion chapter(s) of your thesis, but, generally speaking, such reflection on the meaning of the results should be entirely separate from the factual report of your research findings. There are exceptions, of course, and some candidates, supervisors and departments may prefer the factual presentation and interpretive discussion of results to be blended, just as some thesis topics may demand such treatment, but this is rare and best avoided unless there are persuasive reasons to avoid separating the facts from your thoughts about them. If you do find that you need to blend facts and interpretation in reporting your results, make sure that your language leaves no doubt about the line between the two: words such as ‘seems,’ ‘appears,’ ‘may,’ ‘might,’ probably’ and the like will effectively distinguish analytical speculation from more factual reporting (see also Section 4.5).

You need not dedicate much space in this part of the thesis to the methods you used to arrive at your results because these have already been described in your methodology chapter(s), but they can certainly be revisited briefly to clarify or lend structure to your report. Results are most often presented in a straightforward narrative form which is often supplemented by tables and perhaps by figures such as graphs, charts and maps. An effective approach is to decide immediately which information would be best included in tables and figures, and then to prepare those tables and figures before you begin writing the text for the chapter (see Section 4.4.1 on designing effective tables and figures). Arranging your data into the visually immediate formats provided by tables and figures can, for one, produce interesting surprises by enabling you to see trends and details that you may not have noticed previously, and writing the report of your results will prove easier when you have the tables and figures to work with just as your readers ultimately will. In addition, while the text of the results chapter(s) should certainly highlight the most notable data included in tables and figures, it is essential not to repeat information unnecessarily, so writing with the tables and figures already constructed will help you keep repetition to a minimum. Finally, writing about the tables and figures you create will help you test their clarity and effectiveness for your readers, and you can make any necessary adjustments to the tables and figures as you work. Be sure to refer to each table and figure by number in your text and to make it absolutely clear what you want your readers to see or understand in the table or figure (e.g., ‘see Table 1 for the scores’ and ‘Figure 2 shows this relationship’).

Beyond combining textual narration with the data presented in tables and figures, you will need to organise your report of the results in a manner best suited to the material. You may choose to arrange the presentation of your results chronologically or in a hierarchical order that represents their importance; you might subdivide your results into sections (or separate chapters if there is a great deal of information to accommodate) focussing on the findings of different kinds of methodology (quantitative versus qualitative, for instance) or of different tests, trials, surveys, reviews, case studies and so on; or you may want to create sections (or chapters) focussing on specific themes, patterns or categories or on your research questions and/or hypotheses. The last approach allows you to cluster results that relate to a particular question or hypothesis into a single section and can be particularly useful because it provides cohesion for the thesis as a whole and forces you to focus closely on the issues central to the topic, problem or phenomenon you are investigating. You will, for instance, be able to refer back to the questions and hypotheses presented in your introduction (see Section 3.1), to answer the questions and confirm or dismiss the hypotheses and to anticipate in relation to those questions and hypotheses the discussion and interpretation of your findings that will appear in the next part of the thesis (see Section 4.5). Less effective is an approach that organises the presentation of results according to the items of a survey or questionnaire, because these lend the structure of the instrument used to the results instead of connecting those results directly to the aims, themes and argument of your thesis, but such an organisation can certainly be an important early step in your analysis of the findings and might even be valid for the final thesis if, for instance, your work focuses on developing the instrument involved.

The results generated by doctoral research are unique, and this book cannot hope to outline all the possible approaches for presenting the data and analyses that constitute research results, but it is essential that you devote considerable thought and special care to the way in which you structure the report of your results (Section 6.1 on headings may prove helpful). Whatever structure you choose should accurately reflect the nature of your results and highlight their most important and interesting trends, and it should also effectively allow you (in the next part of the thesis) to discuss and speculate upon your findings in ways that will test the premises of your study, work well in the overall argument of your thesis and lead to significant implications for your research. Regardless of how you organise the main body of your results chapter(s), however, you should include a final paragraph (or more than one paragraph if necessary) that briefly summarises and explains the key results and also guides the reader on to the discussion and interpretation of those results in the following chapter(s).

Why PhD Success?

To Graduate Successfully

This article is part of a book called "PhD Success" which focuses on the writing process of a phd thesis, with its aim being to provide sound practices and principles for reporting and formatting in text the methods, results and discussion of even the most innovative and unique research in ways that are clear, correct, professional and persuasive.

The assumption of the book is that the doctoral candidate reading it is both eager to write and more than capable of doing so, but nonetheless requires information and guidance on exactly what he or she should be writing and how best to approach the task. The basic components of a doctoral thesis are outlined and described, as are the elements of complete and accurate scholarly references, and detailed descriptions of writing practices are clarified through the use of numerous examples.

The basic components of a doctoral thesis are outlined and described, as are the elements of complete and accurate scholarly references, and detailed descriptions of writing practices are clarified through the use of numerous examples. PhD Success provides guidance for students familiar with English and the procedures of English universities, but it also acknowledges that many theses in the English language are now written by candidates whose first language is not English, so it carefully explains the scholarly styles, conventions and standards expected of a successful doctoral thesis in the English language.

Individual chapters of this book address reflective and critical writing early in the thesis process; working successfully with thesis supervisors and benefiting from commentary and criticism; drafting and revising effective thesis chapters and developing an academic or scientific argument; writing and formatting a thesis in clear and correct scholarly English; citing, quoting and documenting sources thoroughly and accurately; and preparing for and excelling in thesis meetings and examinations. 

Completing a doctoral thesis successfully requires long and penetrating thought, intellectual rigour and creativity, original research and sound methods (whether established or innovative), precision in recording detail and a wide-ranging thoroughness, as much perseverance and mental toughness as insight and brilliance, and, no matter how many helpful writing guides are consulted, a great deal of hard work over a significant period of time. Writing a thesis can be an enjoyable as well as a challenging experience, however, and even if it is not always so, the personal and professional rewards of achieving such an enormous goal are considerable, as all doctoral candidates no doubt realise, and will last a great deal longer than any problems that may be encountered during the process.

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Rene Tetzner

Rene Tetzner's blog posts dedicated to academic writing. Although the focus is on How To Write a Doctoral Thesis, many other important aspects of research-based writing, editing and publishing are addressed in helpful detail.

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Home » Chapter Summary & Overview – Writing Guide and Examples

Chapter Summary & Overview – Writing Guide and Examples

Table of Contents

Chapter Summary

Chapter summary is a brief overview of the key points or events covered in a specific chapter of a book, academic paper, or other written work. It typically includes a concise description of the main ideas, arguments, or themes explored in the chapter, as well as any important supporting details or evidence .

Chapter summaries are often used as study aids, providing readers with a quick way to review and understand the content of a particular section of a longer work. They may also be included as part of a book’s table of contents or used as a promotional tool to entice potential readers.

How to Write Chapter Summary

Writing a chapter summary involves condensing the content of a chapter into a shorter, more concise form while still retaining its essential meaning. Here are some steps to help you write a chapter summary:

• Read the chapter carefully: Before summarizing a chapter, it is important to read it thoroughly to ensure that you understand the main ideas and points being made.
• Identify the main ideas: Identify the main ideas and arguments that the chapter is presenting. These may be explicit, or they may be implicit and require some interpretation on your part.
• Make notes: Take notes while reading to help you keep track of the main ideas and arguments. Write down key phrases, important quotes, and any examples or evidence that support the main points.
• Create an outline : Once you have identified the main ideas and arguments, create an outline for your summary. This will help you organize your thoughts and ensure that you include all the important points.
• Write the summary : Using your notes and outline, write a summary of the chapter. Start with a brief introduction that provides context for the chapter, then summarize the main ideas and arguments, and end with a conclusion that ties everything together.
• Edit and revise: After you have written the summary, review it carefully to ensure that it is accurate and concise. Make any necessary edits or revisions to improve the clarity and readability of the summary.
• Check for plagiarism : Finally, check your summary for plagiarism. Make sure that you have not copied any content directly from the chapter without proper citation.

Chapter Summary in Research Paper

In a Research Paper , a Chapter Summary is a brief description of the main points or findings covered in a particular chapter. The summary is typically included at the beginning or end of each chapter and serves as a guide for the reader to quickly understand the content of that chapter.

Here is an example of a chapter summary from a research paper on climate change:

Chapter 2: The Science of Climate Change

In this chapter, we provide an overview of the scientific consensus on climate change. We begin by discussing the greenhouse effect and the role of greenhouse gases in trapping heat in the atmosphere. We then review the evidence for climate change, including temperature records, sea level rise, and changes in the behavior of plants and animals. Finally, we examine the potential impacts of climate change on human society and the natural world. Overall, this chapter provides a foundation for understanding the scientific basis for climate change and the urgency of taking action to address this global challenge.

Chapter Summary in Thesis

In a Thesis , the Chapter Summary is a section that provides a brief overview of the main points covered in each chapter of the thesis. It is usually included at the beginning or end of each chapter and is intended to help the reader understand the key concepts and ideas presented in the chapter.

For example, in a thesis on computer science field, a chapter summary for a chapter on “Machine Learning Algorithms” might include:

Chapter 3: Machine Learning Algorithms

This chapter explores the use of machine learning algorithms in solving complex problems in computer science. We begin by discussing the basics of machine learning, including supervised and unsupervised learning, as well as different types of algorithms such as decision trees, neural networks, and support vector machines. We then present a case study on the application of machine learning algorithms in image recognition, demonstrating how these algorithms can improve accuracy and reduce error rates. Finally, we discuss the limitations and challenges of using machine learning algorithms, including issues of bias and overfitting. Overall, this chapter highlights the potential of machine learning algorithms to revolutionize the field of computer science and drive innovation in a wide range of industries.

Examples of Chapter Summary

Some Examples of Chapter Summary are as follows:

Research Title: “The Impact of Social Media on Mental Health: A Review of the Literature”

Chapter Summary:

Chapter 1: Introduction

This chapter provides an overview of the research problem, which is the impact of social media on mental health. It presents the purpose of the study, the research questions, and the methodology used to conduct the research.

Research Title : “The Effects of Exercise on Cognitive Functioning in Older Adults: A Meta-Analysis”

Chapter 2: Literature Review

This chapter reviews the existing literature on the effects of exercise on cognitive functioning in older adults. It provides an overview of the theoretical framework and previous research findings related to the topic. The chapter concludes with a summary of the research gaps and limitations.

Research Title: “The Role of Emotional Intelligence in Leadership Effectiveness: A Case Study of Successful Business Leaders”

Chapter 3: Methodology

This chapter presents the research methodology used in the study, which is a case study approach. It describes the selection criteria for the participants and the data collection methods used. The chapter also provides a detailed explanation of the data analysis techniques used in the study.

Research Title: “Factors Influencing Employee Engagement in the Workplace: A Systematic Review”

Chapter 4: Results and Discussion

This chapter presents the findings of the systematic review on the factors influencing employee engagement in the workplace. It provides a detailed analysis of the results, including the strengths and limitations of the studies reviewed. The chapter also discusses the implications of the findings for practice and future research.

Purpose of Chapter Summary

Some Purposes of the Chapter Summary are as follows:

• Comprehension : A chapter summary can help readers understand the main points of a chapter or book. It can help readers remember important details, keep track of the plot or argument, and connect the key ideas.
• Review : A chapter summary can be a useful tool for reviewing the material covered in a chapter. It can help readers review the content quickly and efficiently, and it can also serve as a reference for future study.
• Study aid: A chapter summary can be used as a study aid, especially for students who are preparing for exams or writing papers. It can help students organize their thoughts and focus on the most important information.
• Teaching tool: A chapter summary can be a useful teaching tool for educators. It can help teachers introduce key concepts and ideas, facilitate class discussion, and assess student understanding.
• Communication : A chapter summary can be used as a way to communicate the main ideas of a chapter or book to others. It can be used in presentations, reports, and other forms of communication to convey important information quickly and concisely.
• Time-saving : A chapter summary can save time for busy readers who may not have the time to read an entire book or chapter in detail. By providing a brief overview of the main points, a chapter summary can help readers determine whether a book or chapter is worth further reading.
• Accessibility : A chapter summary can make complex or technical information more accessible to a wider audience. It can help break down complex ideas into simpler terms and provide a clear and concise explanation of key concepts.
• Analysis : A chapter summary can be used as a starting point for analysis and discussion. It can help readers identify themes, motifs, and other literary devices used in the chapter or book, and it can serve as a jumping-off point for further analysis.
• Personal growth : A chapter summary can be used for personal growth and development. It can help readers gain new insights, learn new skills, and develop a deeper understanding of the world around them.

When to Write Chapter Summary

Chapter summaries are usually written after you have finished reading a chapter or a book. Writing a chapter summary can be useful for several reasons, including:

• Retention : Summarizing a chapter helps you to better retain the information you have read.
• Studying : Chapter summaries can be a useful study tool when preparing for exams or writing papers.
• Review : When you need to review a book or chapter quickly, a summary can help you to refresh your memory.
• Analysis : Summarizing a chapter can help you to identify the main themes and ideas of a book, which can be useful when analyzing it.

Advantages of Chapter Summary

Chapter summaries have several advantages:

• Helps with retention : Summarizing the key points of a chapter can help you remember important information better. By condensing the information, you can identify the main ideas and focus on the most relevant points.
• Saves time : Instead of re-reading the entire chapter when you need to review information, a summary can help you quickly refresh your memory. It can also save time during note-taking and studying.
• Provides an overview : A summary can give you a quick overview of the chapter’s content and help you identify the main themes and ideas. This can help you understand the broader context of the material.
• Helps with comprehension : Summarizing the content of a chapter can help you better understand the material. It can also help you identify any areas where you might need more clarification or further study.
• Useful for review: Chapter summaries can be a useful review tool before exams or when writing papers. They can help you organize your thoughts and review key concepts and ideas.
• Facilitates discussion: When working in a group, chapter summaries can help facilitate discussion and ensure that everyone is on the same page. It can also help to identify areas of confusion or disagreement.
• Supports active reading : Creating a summary requires active reading, which means that you are engaging with the material and thinking critically about it. This can help you develop stronger reading and critical thinking skills.
• Enables comparison : When reading multiple sources on a topic, creating summaries of each chapter can help you compare and contrast the information presented. This can help you identify differences and similarities in the arguments and ideas presented.
• Helpful for long texts: In longer books or texts, chapter summaries can be especially helpful. They can help you break down the material into manageable chunks and make it easier to digest.

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Thesis Analysis

What is your general topic or what problem area are you interested in? How would you express it in a few words?

What central question are you trying to answer about your topic?

What do you think is the best answer to your central question? From your research so far, what have you concluded? What is your main point about your topic?

In one sentence, how would you describe your findings to someone who asked you about your research?

How does your idea differ from other views you have read? What do you have to say about your topic that is new?

Ask why? And how? Of what seems like a thesis statement when it begins to emerge. What relationship exists between the ideas you are describing? For example, are you suggesting that one idea causes another? Contradicts another? Subsumes another?

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How to Write Discussion Part of Thesis

January 13 2021 11:07 AM

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How to Write a Discussion (Analysis) Chapter in a Thesis

Discussion and analysis are probably the most critical components of any thesis. These are also the longest sections of your thesis, which require thoroughness, conciseness, attention to detail, brevity, and extensive use of primary and secondary evidence.

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Useful Tips on Writing Correct Thesis Discussion

The article below will help students learn about proper thesis discussion   writing. We will provide you with major objectives and professional approaches to writing. After that, you will have an opportunity to learn about certain steps that can be taken to write a brilliant dissertation discussion chapter.

Objectives and Approaches Writing a Discussion Chapter

Remember the major objectives When writing a dissertation or thesis discussion chapter. You should state your interpretations, declare your point of view, explain the effects of the research findings, and predict and suggest future research work.

Remember that dissertation or thesis discussion   chapter is perceived as the most crucial part of one's work. That is why it is normal for students to cope with this chapter, not for the first time.

Useful Steps for Writing Effective Discussion

It should be precise and short to ensure this chapter is easy to understand. However, the discussion chapter should also state, elaborate, support, provide an explanation and even defend all your logical conclusions. Remember that your writing should not simply repeat the results. It should be a commentary. Do not write about any distracting issues. They will only confuse the reader and hide your message's importance. It is difficult to create a perfect piece of writing, but you should try to make your readers distinguish between facts and speculation.

Follow the below-provided steps, and you will cope with your thesis or dissertation successfully:

• The structure of the discussion chapter should start with specific information and end with general information. It would be best to slowly transition from some narrow confines to the general facts about the selected discipline.
• Write the introduction in a general tone. Using the same main terms, viewpoint, and tense in the introductory paragraphs is easy. 
• You can also rewrite the research questions and restate the hypothesis presented in the introduction. After that, you can provide the answers to the major research questions. Remember that answers should be supported by the research findings.
• Explain the relationship between your results and the expectations of the study and course literature. Please explain why the obtained results can be accepted and how they fit with existing knowledge about the selected subject. Use correct and relevant citations here. 
• Pay close attention to the obtained results related to the posed research questions. It does not matter whether the findings were statistically important.  
• Inform your targeted audience about the principles, patterns, and major relationships detected in your findings, and collect them into one perspective. This information should be sequential. First, give the answer, provide the results, and then cite reliable and academic sources. You can point readers to graphs and figures to enhance the main argument.   
• All your answers should be defended. You can do this in two ways: explain the validity of the answers and present the other answers' shortcomings. By presenting both sides of the argument, you can strengthen your viewpoint.
• The conflicting data should be identified in your work as well. Discuss and assess any explanations that conflict with your results. It can help to win with your targeted audience and make them feel sympathetic to the knowledge offered by your study. 
• Discuss any findings that are perceived as unexpected. Please start with the paragraph related to the finding and provide its description. Identify any potential weaknesses and limitations present in your study. Comment on the significance of the described limitations to your findings and their interpretation. Explain how they can influence their validity. This section cannot have an apologetic tone. Remember that every study has its limitations and weaknesses.    
• It would be best to summarize the findings' main implications (this should be done regardless of statistical importance) and make a few recommendations regarding any further research. 
• You should prove the significance of the study results and their conclusions and describe how they can influence our comprehension of the discussed issue(s).  
• Finally, it would be best to be specific but brief when discussing everything related to the study.

Now you know how to write a discussion paper. We hope that our article inspired you to start writing your paper. You can always find a dissertation discussion example and see its structure.

You cannot write a great thesis   without using a large body of literature. Every claim you make must be supported with credible and verifiable information. The data you provide in these sections will either support or nullify your hypotheses or assumptions. In either case, these results will inform the direction of future research activities.

Consider the requirements for your thesis and ask your thesis supervisor for more detail if you are unsure how much space your discussion and analysis chapter must take. Begin the section with the strongest evidence supporting or refuting your thesis. If you have any doubts, ask for help, and we will be happy to provide sufficient evidence to support your  conclusions .

While working on your project's analysis and discussion chapters, we will adhere to the rules and requirements provided by your supervisor. We will consider the terms and technical vocabulary that must be used in the body of your thesis. We try not to overload discussions with too many technical words so your readers can understand your conclusions.

Otherwise, we will include a glossary of terms to explain the meaning of the most complicated words. You will not have trouble submitting a perfect thesis on time with our writers!

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Writing a Good Chapter Analysis - Stop Summarizing and Start Analyzing

• Trent Lorcher
• Categories : Help with writing assignments paragraphs, essays, outlines & more
• Tags : Homework help & study guides

Chapter Analysis vs. Summary

Before you learn how to write a good chapter analysis, you need to know what an analysis is. Let’s begin by telling you what it’s not: an analysis is not a summary. While a summary is a stripped down rehash of a chapter covering the main plot points, an analysis involves using specific evidence from the text and explaining how it relates to a particular theme of what you’re reading. It also involves explaining the author’s purpose for using specific elements of literature.

One Step at a Time

I’m going to make this easy for you with a step-by-step process for writing a good chapter analysis. Step 1 : Read the chapter. I sincerely hope you’ve already done this, especially if the assignment’s due in 15 minutes. Step 2 : Read the chapter and annotate. “But wait,” you protest. “I’ve already read the chapter. Now you want me to do it again?” You clicked here because you want to write a good chapter analysis. If you want to write a bad chapter analysis then go to YouTube, listen to your favorite song, and write your analysis without my help. This time, read the chapter with a critical eye. Highlight and mark things you feel are important. This is called annotation. Knowing how to annotate (although the link is for annotating a poem, it will help you annotate non-poems, and yes, you should read it) will provide years of good grades in English class. Step 3 : Create a thesis statement. If you don’t know how to write a thesis statement , now would be the perfect time to learn (you’ll thank me for this). Your thesis statement must contain a subject and an opinion. The subject is the chapter you’re analyzing. Your opinion must contain how the chapter contributes to the overall theme of the work or what the author’s purpose is in using certain literary devices. You probably want examples. Here they are:

• Chapter 4 of The Chocolate War by Robert Cormier uses an ironic relationship between Trinity High School’s most feared teacher and Trinity High School’s most disobedient student to foreshadow the imminent destruction of all that is good at the school.
• The final chapter in J.K. Rowling’s Harry Potter and the Deathly Hallows firmly establishes Harry as a Messianic figure and a symbol of hope in a world of darkness.
• Chapter 5 of John Steinbeck’s Of Mice and Men resolves the novel’s main conflict–the individual vs. society–with society crushing the individual.

Do not overlook the importance of creating a sound thesis statement. Everything you write from this point forward hinges on its success. Once you’ve written thesis statement, you can begin the outline.

Plan Your Success With an Outline

Learning how to write a good chapter or book analysis means learning how to write a good outline. Step 4 : Make an outline - “But wait,” you protest. “You want me to write an outline? I just want to get this thing done.” Once again, you want to write a good analysis, right? Here are the steps to making a good outline. We’ll assume the outline is for a multi-paragraph essay.

I. Your thesis statement goes here. For the sake of this example, we’ll use the one above from The Chocolate War .

A. Write a topic sentence for your first body paragraph here. Your topic sentence must support your thesis statement. If you don’t know how to write a topic sentence , now would be a good time to find out (you’ll thank me for this, too). Example : Brother Leon’s association with the Vigils undermines his ability to provide a safe environment for his students.

1. Write your first piece of evidence here. Your evidence , by the way, comes from the chapter. It can be a direct quotation, a specific fact, or a brief summary. Don’t bog the reader down with unnecessarily long quotes or useless facts. Example : Brother Leon gives tacit approval and open support for the most dangerous student organization at his school in return for their support of the annual chocolate sale.

a. Give an explanation of how your fact supports the topic sentence. This explanation can be an opinion, insight, interpretation, analysis (it’s a good idea to have analysis in your analysis paper), analogy, or anecdote. Example : This would be the equivalent of a high school principal enlisting the help of the neighborhood Bloods or Crips to ensure attendance at the school’s choir concert.

b. Continue your explanation or provide an additional related explanation. Example : This new alliance will eventually yield tragic results.

2. Write your second piece of evidence here. Example : Brother Leon claims the importance of the chocolate sale is to keep the school afloat financially.

a. Provide an explanation for fact #2. Example : If Brother Leon truly cared about the school, he would not lend his support to the school’s most malicious organization .

b. Continue your explanation or provide an additional related explanation. Example : Most likely, Brother Leon will receive a personal financial benefit from the sale of the chocolates.

3. Write a concluding sentence here that transitions into the next paragraph. Example : Brother Leon thinks he’s manipulating Archie, but the reader knows otherwise.

B. Here would be the topic sentence of your second body paragraph. Judging by the concluding sentence of your first body paragraph, this paragraph will treat Archie’s ability as a leader and manipulator and its likely potential for tragedy. This paragraph and each succeeding paragraph will follow the same exact pattern as the first body paragraph.

The more thorough your outline, the easier it will be to write your chapter analysis. Now that your outline is complete, it’s time to write.

You’re Almost Done

If you’ve done steps 1-4 correctly, you’ve almost guaranteed yourself an insightful analysis and a very good grade. Step 5: Write the First Draft - If you wrote a good outline, this part is easy. Begin with an attention grabber in the introduction . Your best bet here would be to provide a brief summary of the chapter on which you’re writing–a couple of sentences should be sufficient–followed by your already written thesis statement (Your thesis statement should be the last sentence of your introduction). Your body paragraphs are practically written already. Add transitions for fluency. Reword, if necessary. Add words for clarity. Subtract words, if possible (just because it’s in the outline doesn’t mean it has to be in your paper). Step 6 : Edit and Revise - Proofread for grammar and punctuation errors. Other things to check when revising include:

• making sure you haven’t written a summary.
• making sure what you wrote makes sense.
• making sure your body paragraphs support your thesis statement.
• making sure you’ve covered all aspects of the assignment.

Step 7 : Turn it in. If you’ve followed these steps, you can turn it in with a smug look on your face. Sit up straight and let the class know how awesome you are. Congratulations, you’ve just succeeded at one of the hardest assignments you’ll get in an English class.

The author has taught English for 13 years. Image by TeroVesalainen from Pixabay

This post is part of the series: Writing Made Easy

Writing isn’t as hard as you think.

• How to Make an Outline: Components of the Writing Process
• How to Write in the Active Voice & When to Write in Passive Voice
• Getting Technical With Technical Writing
• Analyze This: Write a Chapter Analysis that Will Amaze Your Teacher

What’s Included: Discussion Template

This template covers all the core components required in the discussion/analysis chapter of a typical dissertation or thesis, including:

• The opening/overview section
• Overview of key findings
• Interpretation of the findings
• Concluding summary

The purpose of each section is explained in plain language, followed by an overview of the key elements that you need to cover. The template also includes practical examples to help you understand exactly what’s required, along with links to additional free resources (articles, videos, etc.) to help you along your research journey.

The cleanly formatted Google Doc can be downloaded as a fully editable MS Word Document (DOCX format), so you can use it as-is or convert it to LaTeX.

PS – if you’d like a high-level template for the entire thesis, you can we’ve got that too .

FAQ: Thesis Discussion Template

What types of dissertations/theses can this template be used for.

The discussion chapter template follows the standard format for academic research projects, which means it will be suitable for the majority of dissertations, theses and research projects (especially those within the sciences).

Keep in mind that the exact requirements for the discussion chapter/section will vary between universities and degree programs. For example, your university may require that the discussion chapter and conclusion chapter are merged into one, or that the results and discussion are covered together (this is often the case with qualitative research). So, be sure to double-check your university’s requirements before you finalise your structure.

Is this template for an undergrad, Master or PhD-level thesis?

This template can be used for a dissertation, thesis or research project at any level of study. Doctoral-level projects typically require the discussion chapter to be more extensive/comprehensive, but the structure will typically remain the same. Again, be sure to check your university’s requirements and norms in terms of document structure.

How long should the discussion chapter be?

This can vary a fair deal, depending on the level of study (undergrad, Master or Doctoral), the field of research, as well as your university’s specific requirements. Therefore, it’s best to check with your university or review past dissertations from your program to get an accurate estimate.

Can I share this template with my friends/colleagues?

Yes, you’re welcome to share this template in its original format (no editing allowed). If you want to post about it on your blog or social media, please reference this page as your source.

What format is the template (DOC, PDF, PPT, etc.)?

The dissertation discussion chapter template is provided as a Google Doc. You can download it in MS Word format or make a copy to your Google Drive. You’re also welcome to convert it to whatever format works best for you, such as LaTeX or PDF.

Do you have templates for the other chapters?

Yes, we do. We are constantly developing our collection of free resources to help students complete their dissertations and theses. You can view all of our template resources here .

Can Grad Coach help me with my discussion/analysis?

Yes, we can provide coaching-based assistance with your discussion chapter (or any other chapter). If you’re interested, get in touch to discuss our private coaching services .

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Mastering Dissertation Data Analysis: A Comprehensive Guide

By Laura Brown on 29th December 2023

To craft an effective dissertation data analysis chapter, you need to follow some simple steps:

• Start by planning the structure and objectives of the chapter.
• Clearly set the stage by providing a concise overview of your research design and methodology.
• Proceed to thorough data preparation, ensuring accuracy and organisation.
• Justify your methods and present the results using visual aids for clarity.
• Discuss the findings within the context of your research questions.
• Finally, review and edit your chapter to ensure coherence.

This approach will ensure a well-crafted and impactful analysis section.

Before delving into details on how you can come up with an engaging data analysis show in your dissertation, we first need to understand what it is and why it is required.

What Is Data Analysis In A Dissertation?

The data analysis chapter is a crucial section of a research dissertation that involves the examination, interpretation, and synthesis of collected data. In this chapter, researchers employ statistical techniques, qualitative methods, or a combination of both to make sense of the data gathered during the research process.

Why Is The Data Analysis Chapter So Important?

The primary objectives of the data analysis chapter are to identify patterns, trends, relationships, and insights within the data set. Researchers use various tools and software to conduct a thorough analysis, ensuring that the results are both accurate and relevant to the research questions or hypotheses. Ultimately, the findings derived from this chapter contribute to the overall conclusions of the dissertation, providing a basis for drawing meaningful and well-supported insights.

Steps Required To Craft Data Analysis Chapter To Perfection

Now that we have an idea of what a dissertation analysis chapter is and why it is necessary to put it in the dissertation, let’s move towards how we can create one that has a significant impact. Our guide will move around the bulleted points that have been discussed initially in the beginning. So, it’s time to begin.

Step 1: Planning Your Data Analysis Chapter

Planning your data analysis chapter is a critical precursor to its successful execution.

• Begin by outlining the chapter structure to provide a roadmap for your analysis.
• Start with an introduction that succinctly introduces the purpose and significance of the data analysis in the context of your research.
• Following this, delineate the chapter into sections such as Data Preparation, where you detail the steps taken to organise and clean your data.
• Plan on to clearly define the Data Analysis Techniques employed, justifying their relevance to your research objectives.
• As you progress, plan for the Results Presentation, incorporating visual aids for clarity. Lastly, earmark a section for the Discussion of Findings, where you will interpret results within the broader context of your research questions.

This structured approach ensures a comprehensive and cohesive data analysis chapter, setting the stage for a compelling narrative that contributes significantly to your dissertation. You can always seek our dissertation data analysis help to plan your chapter.

Step 2: Setting The Stage – Introduction to Data Analysis

Your primary objective is to establish a solid foundation for the analytical journey. You need to skillfully link your data analysis to your research questions, elucidating the direct relevance and purpose of the upcoming analysis.

Simultaneously, define key concepts to provide clarity and ensure a shared understanding of the terms integral to your study. Following this, offer a concise overview of your data set characteristics, outlining its source, nature, and any noteworthy features.

This meticulous groundwork alongside our help with dissertation data analysis lays the base for a coherent and purposeful chapter, guiding readers seamlessly into the subsequent stages of your dissertation.

Step 3: Data Preparation

Now this is another pivotal phase in the data analysis process, ensuring the integrity and reliability of your findings. You should start with an insightful overview of the data cleaning and preprocessing procedures, highlighting the steps taken to refine and organise your dataset. Then, discuss any challenges encountered during the process and the strategies employed to address them.

Moving forward, delve into the specifics of data transformation procedures, elucidating any alterations made to the raw data for analysis. Clearly describe the methods employed for normalisation, scaling, or any other transformations deemed necessary. It will not only enhance the quality of your analysis but also foster transparency in your research methodology, reinforcing the robustness of your data-driven insights.

Step 4: Data Analysis Techniques

The data analysis section of a dissertation is akin to choosing the right tools for an artistic masterpiece. Carefully weigh the quantitative and qualitative approaches, ensuring a tailored fit for the nature of your data.

Quantitative Analysis

• Descriptive Statistics: Paint a vivid picture of your data through measures like mean, median, and mode. It’s like capturing the essence of your data’s personality.
• Inferential Statistics:Take a leap into the unknown, making educated guesses and inferences about your larger population based on a sample. It’s statistical magic in action.

Qualitative Analysis

• Thematic Analysis: Imagine your data as a novel, and thematic analysis as the tool to uncover its hidden chapters. Dissect the narrative, revealing recurring themes and patterns.
• Content Analysis: Scrutinise your data’s content like detectives, identifying key elements and meanings. It’s a deep dive into the substance of your qualitative data.

Providing Rationale for Chosen Methods

You should also articulate the why behind the chosen methods. It’s not just about numbers or themes; it’s about the story you want your data to tell. Through transparent rationale, you should ensure that your chosen techniques align seamlessly with your research goals, adding depth and credibility to the analysis.

Step 5: Presentation Of Your Results

You can simply break this process into two parts.

a.    Creating Clear and Concise Visualisations

Effectively communicate your findings through meticulously crafted visualisations. Use tables that offer a structured presentation, summarising key data points for quick comprehension. Graphs, on the other hand, visually depict trends and patterns, enhancing overall clarity. Thoughtfully design these visual aids to align with the nature of your data, ensuring they serve as impactful tools for conveying information.

b.    Interpreting and Explaining Results

Go beyond mere presentation by providing insightful interpretation by taking data analysis services for dissertation. Show the significance of your findings within the broader research context. Moreover, articulates the implications of observed patterns or relationships. By weaving a narrative around your results, you guide readers through the relevance and impact of your data analysis, enriching the overall understanding of your dissertation’s key contributions.

Step 6: Discussion of Findings

While discussing your findings and dissertation discussion chapter , it’s like putting together puzzle pieces to understand what your data is saying. You can always take dissertation data analysis help to explain what it all means, connecting back to why you started in the first place.

Be honest about any limitations or possible biases in your study; it’s like showing your cards to make your research more trustworthy. Comparing your results to what other smart people have found before you adds to the conversation, showing where your work fits in.

Looking ahead, you suggest ideas for what future researchers could explore, keeping the conversation going. So, it’s not just about what you found, but also about what comes next and how it all fits into the big picture of what we know.

Step 7: Writing Style and Tone

In order to perfectly come up with this chapter, follow the below points in your writing and adjust the tone accordingly,

• Use clear and concise language to ensure your audience easily understands complex concepts.
• Avoid unnecessary jargon in data analysis for thesis, and if specialised terms are necessary, provide brief explanations.
• Keep your writing style formal and objective, maintaining an academic tone throughout.
• Avoid overly casual language or slang, as the data analysis chapter is a serious academic document.
• Clearly define terms and concepts, providing specific details about your data preparation and analysis procedures.
• Use precise language to convey your ideas, minimising ambiguity.
• Follow a consistent formatting style for headings, subheadings, and citations to enhance readability.
• Ensure that tables, graphs, and visual aids are labelled and formatted uniformly for a polished presentation.
• Connect your analysis to the broader context of your research by explaining the relevance of your chosen methods and the importance of your findings.
• Offer a balance between detail and context, helping readers understand the significance of your data analysis within the larger study.
• Present enough detail to support your findings but avoid overwhelming readers with excessive information.
• Use a balance of text and visual aids to convey information efficiently.
• Maintain reader engagement by incorporating transitions between sections and effectively linking concepts.
• Use a mix of sentence structures to add variety and keep the writing engaging.
• Eliminate grammatical errors, typos, and inconsistencies through thorough proofreading.
• Consider seeking feedback from peers or mentors to ensure the clarity and coherence of your writing.

You can seek a data analysis dissertation example or sample from CrowdWriter to better understand how we write it while following the above-mentioned points.

Step 8: Reviewing and Editing

Reviewing and editing your data analysis chapter is crucial for ensuring its effectiveness and impact. By revising your work, you refine the clarity and coherence of your analysis, enhancing its overall quality.

Seeking feedback from peers, advisors or dissertation data analysis services provides valuable perspectives, helping identify blind spots and areas for improvement. Addressing common writing pitfalls, such as grammatical errors or unclear expressions, ensures your chapter is polished and professional.

Taking the time to review and edit not only strengthens the academic integrity of your work but also contributes to a final product that is clear, compelling, and ready for scholarly scrutiny.

Concluding On This Data Analysis Help

Be it master thesis data analysis, an undergraduate one or for PhD scholars, the steps remain almost the same as we have discussed in this guide. The primary focus is to be connected with your research questions and objectives while writing your data analysis chapter.

Do not lose your focus and choose the right analysis methods and design. Make sure to present your data through various visuals to better explain your data and engage the reader as well. At last, give it a detailed read and seek assistance from experts and your supervisor for further improvement.

Laura Brown, a senior content writer who writes actionable blogs at Crowd Writer.

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How to write the analysis and discussion chapters in qualitative (SSAH) research

By charlesworth author services.

• Charlesworth Author Services
• 11 November, 2021

While it is more common for Science, Technology, Engineering and Mathematics (STEM) researchers to write separate, distinct chapters for their data/ results and analysis/ discussion , the same sections can feel less clearly defined for a researcher in Social Sciences, Arts and Humanities (SSAH). This article will look specifically at some useful approaches to writing the analysis and discussion chapters in qualitative/SSAH research.

Note : Most of the differences in approaches to research, writing, analysis and discussion come down, ultimately, to differences in epistemology – how we approach, create and work with knowledge in our respective fields. However, this is a vast topic that deserves a separate discussion.

Look for emerging themes and patterns

The ‘results’ of qualitative research can sometimes be harder to pinpoint than in quantitative research. You’re not dealing with definitive numbers and results in the same way as, say, a scientist conducting experiments that produce measurable data. Instead, most qualitative researchers explore prominent, interesting themes and patterns emerging from their data – that could comprise interviews, textual material or participant observation, for example. 

You may find that your data presents a huge number of themes, issues and topics, all of which you might find equally significant and interesting. In fact, you might find yourself overwhelmed by the many directions that your research could take, depending on which themes you choose to study in further depth. You may even discover issues and patterns that you had not expected , that may necessitate having to change or expand the research focus you initially started off with.

It is crucial at this point not to panic. Instead, try to enjoy the many possibilities that your data is offering you. It can be useful to remind yourself at each stage of exactly what you are trying to find out through this research.

What exactly do you want to know? What knowledge do you want to generate and share within your field?

Then, spend some time reflecting upon each of the themes that seem most interesting and significant, and consider whether they are immediately relevant to your main, overarching research objectives and goals.

Suggestion: Don’t worry too much about structure and flow at the early stages of writing your discussion . It would be a more valuable use of your time to fully explore the themes and issues arising from your data first, while also reading widely alongside your writing (more on this below). As you work more intimately with the data and develop your ideas, the overarching narrative and connections between those ideas will begin to emerge. Trust that you’ll be able to draw those links and craft the structure organically as you write.

Let your data guide you

A key characteristic of qualitative research is that the researchers allow their data to ‘speak’ and guide their research and their writing. Instead of insisting too strongly upon the prominence of specific themes and issues and imposing their opinions and beliefs upon the data, a good qualitative researcher ‘listens’ to what the data has to tell them.

Again, you might find yourself having to address unexpected issues or your data may reveal things that seem completely contradictory to the ideas and theories you have worked with so far. Although this might seem worrying, discovering these unexpected new elements can actually make your research much richer and more interesting. 

Suggestion: Allow yourself to follow those leads and ask new questions as you work through your data. These new directions could help you to answer your research questions in more depth and with greater complexity; or they could even open up other avenues for further study, either in this or future research.

Work closely with the literature

As you analyse and discuss the prominent themes, arguments and findings arising from your data, it is very helpful to maintain a regular and consistent reading practice alongside your writing. Return to the literature that you’ve already been reading so far or begin to check out new texts, studies and theories that might be more appropriate for working with any new ideas and themes arising from your data.

Reading and incorporating relevant literature into your writing as you work through your analysis and discussion will help you to consistently contextualise your research within the larger body of knowledge. It will be easier to stay focused on what you are trying to say through your research if you can simultaneously show what has already been said on the subject and how your research and data supports, challenges or extends those debates. By drawing from existing literature , you are setting up a dialogue between your research and prior work, and highlighting what this research has to add to the conversation.

Suggestion : Although it might sometimes feel tedious to have to blend others’ writing in with yours, this is ultimately the best way to showcase the specialness of your own data, findings and research . Remember that it is more difficult to highlight the significance and relevance of your original work without first showing how that work fits into or responds to existing studies. 

In conclusion

The discussion chapters form the heart of your thesis and this is where your unique contribution comes to the forefront. This is where your data takes centre-stage and where you get to showcase your original arguments, perspectives and knowledge. To do this effectively needs you to explore the original themes and issues arising from and within the data, while simultaneously contextualising these findings within the larger, existing body of knowledge of your specialising field. By striking this balance, you prove the two most important qualities of excellent qualitative research : keen awareness of your field and a firm understanding of your place in it.

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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!

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Dissertation Proposal

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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.

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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.

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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?

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Writing a Dissertation Data Analysis the Right Way

Do you want to be a college professor? Most teaching positions at four-year universities and colleges require the applicants to have at least a doctoral degree in the field they wish to teach in. If you are looking for information about the dissertation data analysis, it means you have already started working on yours. Congratulations!

Truth be told, learning how to write a data analysis the right way can be tricky. This is, after all, one of the most important chapters of your paper. It is also the most difficult to write, unfortunately. The good news is that we will help you with all the information you need to write a good data analysis chapter right now. And remember, if you need an original dissertation data analysis example, our PhD experts can write one for you in record time. You’ll be amazed how much you can learn from a well-written example.

OK, But What Is the Data Analysis Section?

Don’t know what the data analysis section is or what it is used for? No problem, we’ll explain it to you. Understanding the data analysis meaning is crucial to understanding the next sections of this blog post.

Basically, the data analysis section is the part where you analyze and discuss the data you’ve uncovered. In a typical dissertation, you will present your findings (the data) in the Results section. You will explain how you obtained the data in the Methodology chapter.

The data analysis section should be reserved just for discussing your findings. This means you should refrain from introducing any new data in there. This is extremely important because it can get your paper penalized quite harshly. Remember, the evaluation committee will look at your data analysis section very closely. It’s extremely important to get this chapter done right.

Learn What to Include in Data Analysis

Don’t know what to include in data analysis? Whether you need to do a quantitative data analysis or analyze qualitative data, you need to get it right. Learning how to analyze research data is extremely important, and so is learning what you need to include in your analysis. Here are the basic parts that should mandatorily be in your dissertation data analysis structure:

• The chapter should start with a brief overview of the problem. You will need to explain the importance of your research and its purpose. Also, you will need to provide a brief explanation of the various types of data and the methods you’ve used to collect said data. In case you’ve made any assumptions, you should list them as well.
• The next part will include detailed descriptions of each and every one of your hypotheses. Alternatively, you can describe the research questions. In any case, this part of the data analysis chapter will make it clear to your readers what you aim to demonstrate.
• Then, you will introduce and discuss each and every piece of important data. Your aim is to demonstrate that your data supports your thesis (or answers an important research question). Go in as much detail as possible when analyzing the data. Each question should be discussed in a single paragraph and the paragraph should contain a conclusion at the end.
• The very last part of the data analysis chapter that an undergraduate must write is the conclusion of the entire chapter. It is basically a short summary of the entire chapter. Make it clear that you know what you’ve been talking about and how your data helps answer the research questions you’ve been meaning to cover.

Dissertation Data Analysis Methods

If you are reading this, it means you need some data analysis help. Fortunately, our writers are experts when it comes to the discussion chapter of a dissertation, the most important part of your paper. To make sure you write it correctly, you need to first ensure you learn about the various data analysis methods that are available to you. Here is what you can – and should – do during the data analysis phase of the paper:

• Validate the data. This means you need to check for fraud (were all the respondents really interviewed?), screen the respondents to make sure they meet the research criteria, check that the data collection procedures were properly followed, and then verify that the data is complete (did each respondent receive all the questions or not?). Validating the data is no as difficult as you imagine. Just pick several respondents at random and call them or email them to find out if the data is valid.

For example, an outlier can be identified using a scatter plot or a box plot. Points (values) that are beyond an inner fence on either side are mild outliers, while points that are beyond an outer fence are called extreme outliers.

• If you have a large amount of data, you should code it. Group similar data into sets and code them. This will significantly simplify the process of analyzing the data later.

For example, the median is almost always used to separate the lower half from the upper half of a data set, while the percentage can be used to make a graph that emphasizes a small group of values in a large set o data.

ANOVA, for example, is perfect for testing how much two groups differ from one another in the experiment. You can safely use it to find a relationship between the number of smartphones in a family and the size of the family’s savings.

Analyzing qualitative data is a bit different from analyzing quantitative data. However, the process is not entirely different. Here are some methods to analyze qualitative data:

You should first get familiar with the data, carefully review each research question to see which one can be answered by the data you have collected, code or index the resulting data, and then identify all the patterns. The most popular methods of conducting a qualitative data analysis are the grounded theory, the narrative analysis, the content analysis, and the discourse analysis. Each has its strengths and weaknesses, so be very careful which one you choose.

Of course, it goes without saying that you need to become familiar with each of the different methods used to analyze various types of data. Going into detail for each method is not possible in a single blog post. After all, there are entire books written about these methods. However, if you are having any trouble with analyzing the data – or if you don’t know which dissertation data analysis methods suits your data best – you can always ask our dissertation experts. Our customer support department is online 24 hours a day, 7 days a week – even during holidays. We are always here for you!

Tips and Tricks to Write the Analysis Chapter

Did you know that the best way to learn how to write a data analysis chapter is to get a great example of data analysis in research paper? In case you don’t have access to such an example and don’t want to get assistance from our experts, we can still help you. Here are a few very useful tips that should make writing the analysis chapter a lot easier:

• Always start the chapter with a short introductory paragraph that explains the purpose of the chapter. Don’t just assume that your audience knows what a discussion chapter is. Provide them with a brief overview of what you are about to demonstrate.
• When you analyze and discuss the data, keep the literature review in mind. Make as many cross references as possible between your analysis and the literature review. This way, you will demonstrate to the evaluation committee that you know what you’re talking about.
• Never be afraid to provide your point of view on the data you are analyzing. This is why it’s called a data analysis and not a results chapter. Be as critical as possible and make sure you discuss every set of data in detail.
• If you notice any patterns or themes in the data, make sure you acknowledge them and explain them adequately. You should also take note of these patterns in the conclusion at the end of the chapter.
• Do not assume your readers are familiar with jargon. Always provide a clear definition of the terms you are using in your paper. Not doing so can get you penalized. Why risk it?
• Don’t be afraid to discuss both the advantage and the disadvantages you can get from the data. Being biased and trying to ignore the drawbacks of the results will not get you far.
• Always remember to discuss the significance of each set of data. Also, try to explain to your audience how the various elements connect to each other.
• Be as balanced as possible and make sure your judgments are reasonable. Only strong evidence should be used to support your claims and arguments. Weak evidence just shows that you did not do your best to uncover enough information to answer the research question.
• Get dissertation data analysis help whenever you feel like you need it. Don’t leave anything to chance because the outcome of your dissertation depends in large part on the data analysis chapter.

Finally, don’t be afraid to make effective use of any quantitative data analysis software you can get your hands on. We know that many of these tools can be quite expensive, but we can assure you that the investment is a good idea. Many of these tools are of real help when it comes to analyzing huge amounts of data.

Final Considerations

Finally, you need to be aware that the data analysis chapter should not be rushed in any way. We do agree that the Results chapter is extremely important, but we consider that the Discussion chapter is equally as important. Why? Because you will be explaining your findings and not just presenting some results. You will have the option to talk about your personal opinions. You are free to unleash your critical thinking and impress the evaluation committee. The data analysis section is where you can really shine.

Also, you need to make sure that this chapter is as interesting as it can be for the reader. Make sure you discuss all the interesting results of your research. Explain peculiar findings. Make correlations and reference other works by established authors in your field. Show your readers that you know that subject extremely well and that you are perfectly capable of conducting a proper analysis no matter how complex the data may be. This way, you can ensure that you get maximum points for the data analysis chapter. If you can’t do a great job, get help ASAP!

Need Some Assistance With Data Analysis?

If you are a university student or a graduate, you may need some cheap help with writing the analysis chapter of your dissertation. Remember, time saving is extremely important because finishing the dissertation on time is mandatory. You should consider our amazing services the moment you notice you are not on track with your dissertation. Also, you should get help from our dissertation writing service in case you can’t do a terrific job writing the data analysis chapter. This is one of the most important chapters of your paper and the supervisor will look closely at it.

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• Dissertation & Thesis Outline | Example & Free Templates

Dissertation & Thesis Outline | Example & Free Templates

Published on June 7, 2022 by Tegan George . Revised on November 21, 2023.

A thesis or dissertation outline is one of the most critical early steps in your writing process . It helps you to lay out and organize your ideas and can provide you with a roadmap for deciding the specifics of your dissertation topic and showcasing its relevance to your field.

Generally, an outline contains information on the different sections included in your thesis or dissertation , such as:

• Your anticipated title
• Your abstract
• Your chapters (sometimes subdivided into further topics like literature review, research methods, avenues for future research, etc.)

In the final product, you can also provide a chapter outline for your readers. This is a short paragraph at the end of your introduction to inform readers about the organizational structure of your thesis or dissertation. This chapter outline is also known as a reading guide or summary outline.

Table of contents

How to outline your thesis or dissertation, dissertation and thesis outline templates, chapter outline example, sample sentences for your chapter outline, sample verbs for variation in your chapter outline, other interesting articles, frequently asked questions about thesis and dissertation outlines.

While there are some inter-institutional differences, many outlines proceed in a fairly similar fashion.

• Working Title
• “Elevator pitch” of your work (often written last).
• Introduce your area of study, sharing details about your research question, problem statement , and hypotheses . Situate your research within an existing paradigm or conceptual or theoretical framework .
• Subdivide as you see fit into main topics and sub-topics.
• Describe your research methods (e.g., your scope , population , and data collection ).
• Present your research findings and share about your data analysis methods.
• Answer the research question in a concise way.
• Interpret your findings, discuss potential limitations of your own research and speculate about future implications or related opportunities.

For a more detailed overview of chapters and other elements, be sure to check out our article on the structure of a dissertation or download our template .

To help you get started, we’ve created a full thesis or dissertation template in Word or Google Docs format. It’s easy adapt it to your own requirements.

 Download Word template    Download Google Docs template

It can be easy to fall into a pattern of overusing the same words or sentence constructions, which can make your work monotonous and repetitive for your readers. Consider utilizing some of the alternative constructions presented below.

Example 1: Passive construction

The passive voice is a common choice for outlines and overviews because the context makes it clear who is carrying out the action (e.g., you are conducting the research ). However, overuse of the passive voice can make your text vague and imprecise.

Example 2: IS-AV construction

You can also present your information using the “IS-AV” (inanimate subject with an active verb ) construction.

A chapter is an inanimate object, so it is not capable of taking an action itself (e.g., presenting or discussing). However, the meaning of the sentence is still easily understandable, so the IS-AV construction can be a good way to add variety to your text.

Example 3: The “I” construction

Another option is to use the “I” construction, which is often recommended by style manuals (e.g., APA Style and Chicago style ). However, depending on your field of study, this construction is not always considered professional or academic. Ask your supervisor if you’re not sure.

Example 4: Mix-and-match

To truly make the most of these options, consider mixing and matching the passive voice , IS-AV construction , and “I” construction .This can help the flow of your argument and improve the readability of your text.

As you draft the chapter outline, you may also find yourself frequently repeating the same words, such as “discuss,” “present,” “prove,” or “show.” Consider branching out to add richness and nuance to your writing. Here are some examples of synonyms you can use.

If you want to know more about AI for academic writing, AI tools, or research bias, make sure to check out some of our other articles with explanations and examples or go directly to our tools!

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When you mention different chapters within your text, it’s considered best to use Roman numerals for most citation styles. However, the most important thing here is to remain consistent whenever using numbers in your dissertation .

The title page of your thesis or dissertation goes first, before all other content or lists that you may choose to include.

A thesis or dissertation outline is one of the most critical first steps in your writing process. It helps you to lay out and organize your ideas and can provide you with a roadmap for deciding what kind of research you’d like to undertake.

• Your chapters (sometimes subdivided into further topics like literature review , research methods , avenues for future research, etc.)

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.

George, T. (2023, November 21). Dissertation & Thesis Outline | Example & Free Templates. Scribbr. Retrieved June 24, 2024, from https://www.scribbr.com/dissertation/dissertation-thesis-outline/

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Chapter 4 – Data Analysis and Discussion (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 – 2964 words

Reliability Analysis

Before conducting any analysis on the data, all the data’s reliability was analyzed based on Cronbach’s Alpha value. The reliability analysis was performed on the complete data of the questionnaire. The reliability of the data was found to be (0.922), as shown in the results of the reliability analysis provided below in table 4.1. However, the complete results output of the reliability analysis is given in the appendix.

Reliability Analysis (N=200)

The Cronbach’s Alpha value between (0.7-1.0) is considered to have excellent reliability. The Cronbach’s Alpha value of the data was found to be (0.922); therefore, this indicated that the questionnaire data had excellent reliability. All of the 29 items of the questionnaire had excellent reliability, and if they are taken for further analysis, they can generate results with 92.2% reliability.

Frequency Distribution Analysis

First of all, the frequency distribution analysis was performed on the demographic variables using SPSS to identify the respondents’ demographic composition. Section 1 of the questionnaire had 5 demographic questions to identify; gender, age group, annual income, marital status, and education level of the research sample. The frequency distribution results shown in table 4.2 below indicated that there were 200 respondents in total, out of which 50% were male, and 50% were female. This shows that the research sample was free from gender-based biases as males and females had equal representation in the sample.

Moreover, the frequency distribution analysis suggested three age groups; ‘20-35’, ‘36-60’ and ‘Above 60’. 39% of the respondents belonged to the ‘20-35’ age group, while 56.5% of the respondents belonged to the ‘36-60’ age group and the remaining 4.5% belonged to the age group of ‘Above 60’.

Furthermore, the annual income level was divided into four categories. The income values were in GBP. It was found that 13% of the respondents had income ‘up to 30000’, 27% had income between ‘31000 to 50000’, 52.5% had income between ‘51000 to 100000’, and 7.5% had income ‘Above 100000’. This suggests that most of the respondents had an annual income between ‘31000 to 50000’ GBP.

The frequency distribution analysis indicated that 61% of respondents were single, while 39% were married, as indicated in table 4.2. This means that most of the respondents were single. Based on frequency distribution, it was also found that the education level of the respondents was analyzed using four categories of education level, namely; diploma, graduate, master, and doctorate. The results depicted that 37% of the respondents were diploma holders, 46% were graduates, 16% had master-level education, while only 2% had a doctorate. This suggests that most of the respondents were either graduate or diploma holders.

Frequency Distribution of the Demographic Characteristics of the respondents (N=200)

Multiple Regression Analysis

The hypotheses were tested using linear multiple regression analysis to determine which of the dependent variables had a significant positive effect on the customer loyalty of the five-star hotel brands. The results of the regression analysis are summarized in the following table 4.3. However, the complete SPSS output of the regression analysis is given in the appendix. Table 4.3

Multiple regression analysis showing the predictive values of dependent variables (Brand image, corporate identity, public relation, perceived quality, and trustworthiness) on customer loyalty (N=200)

Predictors: (Constant), Trustworthiness, Public Relation, Brand Image, Corporate Identity, Perceived Quality Dependent Variable: Customer Loyalty

The significance value (p-value) of ANOVA was found to be (0.000) as shown in the above

table, which was less than 0.05. This suggested that the model equation was significantly fitted

on the data. Moreover, the adjusted R-Square value was (0.897), which indicated that the model’s predictors explained 89.7% variation in customer loyalty.

Furthermore, the presence of the significant effect of the 5 predicting variables on customer loyalty was identified based on their sig. Values. The effect of a predicting variable is significant if its sig. Value is less than 0.05 or if its t-Statistics value is greater than 2. It was found that the variable ‘brand image’ had sig. Value (0.046), the variable ‘corporate identity had sig. Value (0.482), the variable ‘public relation’ had sig. Value (0.400), while the variable ‘perceived quality’ had sig. value (0.000), and the variable ‘trustworthiness’ had sig. value (0.652).

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Hypotheses Assessment

Based on the regression analysis, it was found that brand image and perceived quality have a significant positive effect on customer loyalty. In contrast, corporate identity, public relations, and trustworthiness have an insignificant effect on customer loyalty. Therefore the two hypotheses; H1 and H4 were accepted, however the three hypotheses; H2, H3, and H5 were rejected as indicated in table 4.4.

Hypothesis Assessment Summary Table (N=200)

The insignificant variables (corporate identity, public relation and trustworthiness) were excluded from equation 1. After excluding the insignificant variables from the model equation 1, the final equation becomes as follows;

Customer loyalty                 = α + 0.074 (Brand image) + 0.991 (Perceived quality) + €

The above equation suggests that a 1 unit increase in brand image is likely to result in 0.074 units increase customer loyalty. In comparison, 1 unit increase in perceived quality can result in 0.991 units increase in customer loyalty.

Cross Tabulation Analysis

To further explore the results, the demographic variables’ data were cross-tabulated against the respondents’ responses regarding customer loyalty using SPSS. In this regards the five demographic variables; gender, age group, annual income, marital status and education level were cross-tabulated against the five questions regarding customer loyalty to know the difference between the customer loyalty of five-star hotels of UK based on demographic differences. The results of the cross-tabulation analysis are given in the appendix. The results are graphically presented in bar charts too, which are also given in the appendix.

Cross Tabulation of Gender against Customer Loyalty

The gender was cross-tabulated against question 1 to 5 of the questionnaire to identify the gender differences between male and female respondents’ responses regarding customer loyalty of five-star hotels of the UK. The results indicated that out of 100 males, 57% were extremely agreed that they stay at one hotel, while out of 100 females, 80% were extremely agreed they stay at one hotel. This shows that in comparison with a male, females were more agreed that they stayed at one hotel and were found to be more loyal towards their respective hotel brands.

The cross-tabulation results further indicated that out of 100 males, 53% agreed that they always say positive things about their respective hotel brand to other people. In contrast, out of 100 females, 77% were extremely agreed. Based on the results, the females were found to be in more agreement than males that they always say positive things about their respective hotel brand to other people.

It was further found that out of 100 males, 53% were extremely agreed that they recommend their hotel brand to others, however, out of 100 females, 74% were extremely agreed to this statement. This result also suggested that females were more in agreement than males to recommend their hotel brand to others.

Moreover, it was found that out of 100 males, 54% were extremely agreed that they don’t seek alternative hotel brands, while out of 100 females, 79% were extremely agreed to this statement. This result also suggested that females were more agreed than males that they don’t seek alternative hotel brands, and so were found to be more loyal than males.

Furthermore, it was identified that out of 100 male respondents 56% were extremely agreed that they would continue to go to the same hotel irrespective of the prices, however out of 100 females 79% were extremely agreed. Based on this result, it was clear that females were more agreed than males that they would continue to go to the same hotel irrespective of the prices, so females were found to be more loyal than males.

After cross tabulating ‘gender’ against the response of the 5 questions regarding customer loyalty the females were found to be more loyal customers of the five-star hotel brands than males as they were found to be more in agreement than the man that they stay at one hotel, always say positive things about their hotel brand to other people, recommend their hotel brand to others, don’t seek alternative hotel brands and would continue to go to the same hotel irrespective of the prices.

Cross Tabulation of Age Group against Customer Loyalty

Afterward, the second demographic variable, ‘age groups’ was cross-tabulated against questions 1 to 5 of the questionnaire to identify the difference between the customer loyalty of customers of different age groups. The results indicated that out of 78 respondents between 20 to 35 years of age, 61.5% were extremely agreed that they stayed at one hotel. While out of 113 respondents who were between 36 to 60 years of age, 72.6% were extremely agreed that they always stay at one hotel. However, out of 9 respondents who were above 60 years of age, 77.8% agreed that they always stay at one hotel. This indicated that customers of 36-60 and above 60 age groups were more loyal to their hotel brands as they were keener to stay at a respective hotel brand.

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Cross Tabulation of Annual Income against Customer Loyalty

The third demographic variable, ‘annual income’ was cross-tabulated against questions 1 to 5 of the questionnaire to identify which of the customers were most loyal based on their respective annual income levels. The results indicated that out of 26 respondents who had annual income up to 30000 GBP, 84.6% were extremely agreed that they always stay at one hotel. However, out of 54 respondents who had annual income from 31000 to 50000 GBP, 98.1% agreed that they always stay at one hotel. Although out of 105 respondents had annual income from 50000 to 100000 GBP, 49.5% were extremely agreed that they always stay at one hotel. While out of 10 respondents who had annual income from 50000 to 1000000 GBP, 66.7% agreed that they always stay at one hotel. This indicated that customers of annual income levels from 31000 to 50000 GBP were more loyal to their hotel brands than the customers having other annual income levels.

Cross Tabulation of Marital Status against Customer Loyalty

Furthermore, the fourth demographic variable the ‘marital status’ was cross-tabulated against questions 1 to 5 of the questionnaire to understand the difference between married and unmarried respondents regarding customer loyalty of five-star hotels of the UK. The cross-tabulation analysis results indicated that out of 122 single respondents, 59.8% were extremely agreed that they stay at one hotel. However, out of 78 married respondents, around 82% of respondents agreed that they stay at one hotel. Thus, the married customers were more loyal to their hotel brands than unmarried customers because, in comparison, married customers prefer to stay at one hotel brand.

To proceed with the cross-tabulation results, out of 122 single respondents, 55.7% were extremely agreed upon always saying positive things about their hotel brands to other people. On the other hand, out of 78 married respondents, 79.5% were extremely agreed. Hence, upon evaluating the results, it can be said that married customers have more customer loyalty as they are in more agreement than singles. They always give positive feedback regarding their respective hotel brand to other people.

Cross Tabulation of Education Level against Customer Loyalty

Subsequently, the fifth demographic variable, ‘education level’ was cross-tabulated against questions 1 to 5 of the questionnaire to identify which of the customers were most loyal based on their respective education levels. The results indicated that out of 50 respondents who were diploma holders, 67.6% were extremely agreed that they always stay at one hotel. While out of 64 respondents who were graduates, 69.6% were extremely agreed that they always stay at one hotel. Although out of 22 respondents who were masters, 68.8% were extremely agreed that they always stay at one hotel. However, out of 2 respondents with doctorates, 50% were extremely agreed to always stay at one hotel. This indicated that customers who were graduates were more loyal than the customers with diplomas, masters, or doctorates.

Moreover, 66.2% of the diploma holders were extremely agreed that they always say positive things about their hotel brand to other people. In comparison, 64.1% of the respondents who were graduates were extremely agreed. However, 65.5% of the respondents who had masters were extremely agreed, and 50% of the respondents who had doctorates agreed with the statement. Based on this result customers having masters were the most loyal customers of their respective five-star hotel brands.

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In this subsection, the findings of this study are compared and contrasted with the literature to identify which of the past research supports the present research findings. This present study based on regression analysis suggested that brand image can have a significant positive effect on the customer loyalty of five-star hotels in the UK. This finding was supported by the research of Heung et al. (1996), who also suggested that the hotel’s brand image can play a vital role in preserving a high ratio of customer loyalty.

Moreover, this present study also suggested that perceived quality was the second factor that was found to have a significant positive effect on customer loyalty. The perceived quality was evaluated based on; service quality, comfort, staff courtesy, customer satisfaction, and service quality expectations. In this regard, Tat and Raymond (2000) research supports the findings of this study. The staff service quality was found to affect customer loyalty and the level of satisfaction. Teas (1994) had also found service quality to affect customer loyalty. However, Teas also found that staff empathy (staff courtesy) towards customers can also affect customer loyalty. The research of Rowley and Dawes (1999) also supports the finding of this present study. The users’ expectations about the quality and nature of the services affect customer loyalty. A study by Oberoi and Hales (1990) was found to agree with the present study’s findings, as they had found the quality of staff service to affect customer loyalty.

Summary of the Findings

• The brand image was found to have a significant positive effect on customer loyalty. Therefore customer loyalty is likely to increase with the increase in brand image.
• The corporate identity was found to have an insignificant effect on customer loyalty. Therefore customer loyalty is not likely to increase with the increase in corporate identity.
• Public relations was found to have an insignificant effect on customer loyalty. Therefore customer loyalty is not likely to increase with the increase in public relations.
• Perceived quality was found to have a significant positive effect on customer loyalty. Therefore customer loyalty is likely to increase with the increase in perceived quality.
• Trustworthiness was found to have an insignificant effect on customer loyalty. Therefore customer loyalty is not likely to increase with the increase in trustworthiness.
• The female customers were found to be more loyal customers of the five-star hotel brands than male customers.
• The customers of age from 36 to 60 years were more loyal to their hotel brands than the customers of age from 20 to 35 and above 60.
• The customers who had annual income from 31000 to 50000 were more loyal customers of their respective hotel brands than those who had an annual income level of less than 31000 or more than 50000.
• The married respondents had more customer loyalty than unmarried customers, towards five-star hotel brands of the UK.

The customers who had bachelor degrees and the customers who had master degrees were more loyal to the customers who had a diploma or doctorate.

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.

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

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Articulating Liberation: The Reproductive Justice Fight Against Biopolitical State Violence

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Toward Better Recapitulation of Native Tissues and Tissue Environments

Tissue engineering utilizes polymers, cells, and other bioactive factors to promote regeneration within damaged tissue. The main works in this thesis employ naturally derived polymers for use in tissue engineering and explores ways to recapitulate native environments in vitro .

Collagen (col) is the most prevalent protein in the body. Col type I, II, and III are all fibril-forming collagens that provide structure to tissues. All three types polymerize in vitro to form hydrogels, and these hydrogels have often been studied for use in tissue engineering. Other applications include in vitro tissue models for studies on drug diffusion and drug delivery. Blending collagen types is of particular interest as col I is easier to source and is therefore cheaper than other collagen types. However, to confer biological signals to tissues where col II or III are more abundant (e.g., cartilage or cardiac tissue, respectively), col II or III can be added to col I to form col I/II or col I/III gels, respectively. Additionally, adding multiple types of col to hydrogel models better recapitulates the native environment and can better capture effects on drug diffusion. In this work, compared to col I alone, col I/II hydrogels polymerize more slowly, form more fibril bundles, result in softer hydrogels, and impede transport of larger macromolecules. On the other hand, col I/III gels polymerize at a similar rate to col I, create heterogenous fibril structures, are oftentimes stiffer than col I, and also impede transport of larger macromolecules. Additionally, this work explored the effect of polymerization temperature on blended gel polymerization and properties.

The second work evaluates col I/II hydrogels for a specific application: cartilage tissue engineering for osteoarthritic applications. Col II is the primary protein found in cartilage. Other components include: glycosaminoglycans, such as hyaluronic acid (HA) and chondroitin sulfate, chondrocytes (cartilage cells), and other small signaling molecules. Building on prior work in the group, high molecular weight hyaluronic acid (HA) was added to col I/II hydrogels, and cartilage differentiation of mesenchymal stem cells (MSCs) was assessed under ideal laboratory conditions and under pro-inflammatory, osteoarthritic conditions (i.e., cytokine-supplemented media of oncostatin M (OSM) at 10 ng/mL and tumor necrosis factor-α (TNF-α) at 20 ng/mL). The addition of HA did not dramatically impact cartilage differentiation of MSCs, however, HA did mitigate the effect of inflammation via downregulation of a degradative enzyme. HA had little impact on inflammatory cytokine production of interleukin (IL)-6 or IL-8, both of which are upregulated during osteoarthritis. However, a linear model suggests that HA and IL-8 are strongly correlated. Thus, this system should be explored further with different HA concentrations or presentations (e.g., chemically modified).

The last primary chapter of this thesis provides depth to the pro-inflammatory, osteoarthritic model used in the previous chapter. Different pro-inflammatory environments are studied using cytokines found in OA. MSC pellets (used in literature as controls to confirm chondrogenic potential of MSCs) were used to evaluate these inflammatory environments since MSCs are commonly used in tissue engineering. Six treatments were studied: negative control (without the chondrogenic growth factor TGF-β3), positive control (with the chondrogenic growth factor TGF-β3), and four cytokine treatments all with TGF-β3. First, IL-1β at 10 ng/mL was utilized as a comparison to literature. The other three cytokine groups used TNF-α at 20 ng/mL and OSM at 10 ng/mL individually or combined to form the main experimental group, OSM+TNF-α. All cytokine treatment groups limited cartilage production, but OSM decreased production to a statistically lesser extent than other cytokine groups. This trend was similar to observations made via immunostaining of cartilage matrix and gene expression analysis of aggrecan. Furthermore, OSM+TNF-α statistically lowered aggrecan gene expression. In terms of degradation, when compared to all other groups, OSM dramatically increased the protein expression of the degradative enzyme matrix metalloproteinase-13 (MMP-13). Evaluation of inflammatory markers (IL-6 and IL-8) revealed no signal for OSM-treated pellets. TNF-α yielded some signal after 1 week in culture but no signal after two weeks. IL-1β and OSM+TNF-α both resulted in sustained IL-6 and IL-8 expression, however, IL-1β exhibited large variance. Thus, each cytokine contributes to various pathways that are present in OA. Since the combination of OSM and TNF-α appeared to lower cartilage gene expression and resulted in sustained and reproducible IL-6 and IL-8 production, it may serve as a better model of OA than a single cytokine such as IL-1β.

Degree Type

• Doctor of Philosophy
• Chemical Engineering

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• West Lafayette

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• Tissue engineering

2024 Theses Doctoral

Futurity after the End of History: Chronotopes of Contemporary German Literature, Film, and Music

Wagner, Nathaniel Ross

This dissertation deploys theories of spatiotemporal experience and organization, most prominently Mikhail Bakhtin’s “chronotope,” to set contemporary literature, film, and music into dialogue with theories of post-Wende social and political experiences and possibility that speak, with Francis Fukuyama, as the contemporary as the “End of History.” Where these interlocutors of Fukuyama generally affirm or intensify his view of the contemporary as a time where historical progress slows to a halt, historical memory recedes from view, and the conditions of subjecthood are rephrased from participation in a struggle for progress to mindless consumption and technocratic tinkering, I engage contemporary artwork to flesh out and ultimately peer beyond the boundaries of the real and the possible these social theories articulate. Through a series of close readings of German films, music albums, and novels published between 1995 and 2021, I examine how German authors, filmmakers, and musicians pursue depictions of the malaises of the End of History while also resolutely pointing to the fissures in liberal capitalist hegemony where history—its past and its future—again becomes visible. Mikhail Bakhtin’s notion of the chronotope, a text’s unified expression of space and time, is central to my method of analysis. In tracing the chronotopic contours of contemporary works of music, film, and literature, I argue, we—as readers, viewers, and listeners—are engaged to think and act alongside the forms and figures that populate the worlds their authors create. In doing so, we ultimately uncover forceful accusations, resolute alternatives, and even hopeful antidotes to the deficiencies of our present that help us both to soberly contemplate the implications the pessimistic formulations of contemporary theory have on our lives, communities, and futures but also to formulate possibilities for them that lie beyond their analytical purview.In a series of close readings of my literary, filmic, and musical primary texts, I engage theorists of the post-Cold War, post-Wende contemporary who write about the political order and social conditions emerging out of the triumph of neoliberalism and market capitalism over socialist, communist, and fascist alternatives. The dissertation begins by establishing a wide view of the contemporary, tracing in its first chapter chronotopic resonances of Hartmut Rosa’s “social acceleration” thesis—which locates the aimlessness and alienation of contemporary society within the accelerationist logic of market capitalist modes of production—across the full temporal arc of the contemporary. Pairing Christian Kracht’s Faserland (1995) with Fatma Aydemir's Ellbogen (2017), I argue that the futilities and frustrations of the modern subject, as foretold in Fukuyama’s “End of History” essay and fleshed out in Rosa’s writings on social acceleration, find resonance not only in the wealthy, educated, white protagonist of Faserland’s 1990s, but also in the impoverished, undereducated, Turkish-Kurdish protagonist of Ellbogen some twenty years later. What connects these two accounts across decades and differences in identities, I demonstrate, is not merely a shared sense of alienation and despair, but a shared, underlying chronotopic characterization of the contemporary. These commonalities appear, I demonstrate, when we connect Rosa’s “social acceleration” thesis to diegetic chronotopes of perpetual motion that depict modern subjects’ inability to avail themselves of the ostensibly liberatory potential of liberal capitalism’s accelerated lifeworld. Chapter 2 then considers Byung-Chul Han’s theory of auto-exploitation and the dilemma of the music novel at a time where the rebellion of punk against social integration has been thoroughly incorporated into capitalism. Reading Marc Degens’ Fuckin Sushi (2015), I examine the novel’s concept of “Abrentnern” as a model for personal and communal fulfillment for those who turn to art as a means self-determination in the age of auto-exploitation. Unlike Kracht and Aydemir, however, Degens sees the closing off of historical possibilities for the good life enjoyed by his punk forbears—here, self-determination through transgressive artistic praxis—not as the contemporary subject’s damnation to cyclical patterns of despair but as a challenge to conceive of the good life anew. Working humorously through its hapless protagonist Niels’ repeated attempts to escape the seemingly inevitable for-profit co-option of his sincere artistic efforts, the novel serves to unveil the persistence of blind spots in this regime of totalizing exploitation. What results is an account of the double-edged logic of capitalist productivity’s ostensible totalization of labor-time. Capitalism, Niels unwittingly discovers, is a logic of production so overwhelming that it continuously drives subjects towards the discovery of new alterities that, for a brief time at least, allow subjects once again to slip between the cracks. The third chapter explores a similar phenomenon of halting resistance to the conditions of the capitalist present through the lens of futurity. Here, I push back against Mark Fisher’s theory of the dominance of “Capitalist Realism” in the contemporary aesthetic imagination, identifying and developing the notion of “subtle futurity”—the modest, yet resolute rephrasing of future possibility beyond the “way things are” of the present—in Leif Randt’s Schimmernder Dunst über CobyCounty (2011) In this light, I argue, Randt’s gestures towards a different future, however halting, mark a significant effort to imagine a benevolent form of future possibility within the context of an era often suspected to have been exhausted of its utopian sentiment. The final two chapters turn to past-minded works that more forcefully repudiate notions of the present as static or closed off from the movement of history. Chapter Four considers W.G. Sebald’s 1995 novel, Die Ringe des Saturn, and The Caretaker’s 2012 album, Patience (After Sebald), developing an account of the chronotopic means by which these works revisit materials of the past within the present. Chronotopic motifs of paraphrase—techniques of sampling in The Caretaker and narrative polyphony in Sebald—come together within macro-level chronotopic frameworks of peripatetic movement—looping repetition in The Caretaker and the retracing of bygone journeys in Sebald—to testify to the unanswered questions and unfinished work of history over and against notions of the present as a time where the past has been relegated to mere museum content or nostalgia for bygone ways of living. Where Chapter Four speaks primarily to the formal mechanisms by which the present rediscovers the past, Chapter Five examines two specific chronotopic innovations for thematically engaging constellations of past-present inter-temporality. Both Sharon Dodua Otoo’s 2021 novel, Adas Raum, and Christian Petzold’s 2018 film, Transit, develop chronotopes wherein past and present are intermingled in increasingly inseparable ways. Adas Raum, I demonstrate, is organized spatiotemporally as a nexus of coiled loops—pasts and presents intertwine, heaven and earth are tangled together, and the fates of human beings and even non-human objects follow spatial and temporal trajectories that weave in and out of conventional linear understandings of space and time. In similar fashion, past and present become inseparable in Petzold’s film, an adaptation of the Anna Seghers’ 1944 novel of the same name, through thematic and formal approaches of blurring that blend the plight of refugees of Seghers’ era with those of Petzold’s present day. History, then, appears remarkably robust in these texts, unfolding accounts of how human beings living through their present might take guidance from the generations that preceded them in the struggle for a better world.

• Motion pictures, German
• Germans--Music
• Capitalism in literature
• Social integration
• Neoliberalism
• Twenty-first century
• Future, The, in literature
• Sebald, W. G. (Winfried Georg), 1944-2001
• Bakhtin, M. M. (Mikhail Mikhaĭlovich), 1895-1975
• Petzold, Christian, 1960-
• Fukuyama, Francis
• Kracht, Christian, 1966-
• Rosa, Hartmut, 1965-
• Ringe des Saturn (Sebald, W. G.)
• End of history and the last man (Fukuyama, Francis)

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