Chapter 01
Choose a topic you can actually finish
Most thesis problems begin with a topic that is too big. Test every idea against three questions before you commit:
- Answerable: Can data or evidence settle it, rather than just opinion?
- Measurable: Can you name the variables or themes you would collect?
- Doable: Can you finish it with your time, access and budget?
Narrow it step by step
Example walkthrough:
Hospitals → Operating theatres in private hospitals → Waste segregation compliance in operating theatres of private hospitals in one city.
Topic scoring worksheet
Score each candidate topic from 1 (weak) to 5 (strong). Choose the topic with the highest total, then check the lowest score for any deal-breaker:
| Criterion | Topic A | Topic B | Topic C |
|---|
| Interest: will I still care in six months? | / 5 | / 5 | / 5 |
| Answerable with data or evidence | / 5 | / 5 | / 5 |
| Variables or themes are clear | / 5 | / 5 | / 5 |
| Access to participants or data | / 5 | / 5 | / 5 |
| Fits my time and budget | / 5 | / 5 | / 5 |
| Supervisor can guide it | / 5 | / 5 | / 5 |
| Total (max 30) | / 30 | / 30 | / 30 |
One-page pitch for your supervisor
- Working title in one line.
- Problem: What is unknown or unsolved, and for whom, in two sentences.
- Question: Your draft research question.
- Method: Design, population and how you will collect data.
- Feasibility: Timeline, access and ethics approval needed.
- Ask: The one decision you need from your supervisor.
Chapter 02
Turn it into a clear research question
A good question names who, what and how you will compare or describe. Use these frames and fill in the blanks:
Comparison: Does [factor] differ between [group A] and [group B]?
Relationship: Is [variable 1] related to [variable 2] among [population]?
Description: How common is [condition] among [population]?
Keep objectives matched
Every objective needs a matching method and a matching result. If one has no match, rewrite it or remove it.
| Objective | Hypothesis | Variable(s) & scale | Test or method | Result table |
|---|
| 1. [verb + what] | H1: [prediction] | [e.g. score, interval] | [e.g. independent t-test] | Table 4.1 |
| 2. [verb + what] | H2: [prediction] | [e.g. ordinal, count] | [e.g. Mann-Whitney U] | Table 4.2 |
| 3. [verb + what] | H3: [prediction] | [e.g. categorical] | [e.g. Chi-square test] | Table 4.3 |
Checks before you finalise
- Each objective starts with one measurable verb (compare, measure, identify, assess).
- The hypothesis can be proved wrong by your data.
- The population and setting are stated in the question.
- The method you chose is the simplest one that answers the question.
Chapter 03
Search the literature properly
Do not start with a general search engine and stop at page one. Search academic databases with a plan and keep a log:
- Where: Crossref and OpenAlex for broad coverage, PubMed for health, arXiv for computing and physics.
- How: Combine ideas with
AND, synonyms with OR, and exact phrases in quotes.
- Screen: Title first, then abstract, then full text.
Check every source: Open the real paper and confirm the DOI, authors and year before you cite it. Never cite something you have not directly seen.
Example search string
("biomedical waste" OR "healthcare waste" OR "medical waste") AND (segregation OR compliance OR practices) AND ("operating theatre" OR "operating room")
Reference-manager setup
- Pick one tool (Zotero, Mendeley or EndNote) and stay with it.
- Save every source with its DOI whenever one exists.
- Add a tag for each chapter that uses the source.
- Fix author names and years in the manager, not by hand in the document.
- Before submission, scan for sources missing volume, issue or page numbers.
Chapter 04
Pick a design and a sample
Your question decides your method, not the other way around:
- Quantitative: Numbers and statistical tests, best for comparing and measuring.
- Qualitative: Interviews and themes, best for meaning and experience.
- Mixed: Both, only when each answers a different part of the question.
Do not guess your sample size: Sample size depends on the statistical test, the effect size you expect, and your tolerance for error. Free tools such as G*Power can calculate it, but you must justify the inputs.
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Worked sample-size walkthrough & ethics approval checklist
Get the step-by-step G*Power input walkthrough for common designs, along with the full institutional ethics-approval checklist for surveys and patient-related data.
Chapter 05
Analyse your data without panic
Before any test, clean the data. Most wrong results come from messy data, not hard statistics:
- Code it: Check every variable has labels and the right measurement scale (nominal, ordinal, scale).
- Missing: Count missing data, decide how to handle it transparently, and report your method.
- Outliers: Look at boxplots first; never delete a value just because it is inconvenient.
- Assumptions: Check normality (Shapiro-Wilk) and spread (Levene's test) before running parametric tests.
Reporting results correctly
ANOVA: A one-way ANOVA showed [a significant / no significant] difference between groups, F([df1], [df2]) = [x], p = [x], η² = [x].
Correlation: [Variable 1] and [variable 2] were [positively / negatively] correlated, r([df]) = [x], p = [x].
Chi-square: There was [an / no] association between [A] and [B], χ²([df], N = [x]) = [x], p = [x], Cramer's V = [x].
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SPSS menu-by-menu steps & ready-to-adapt result tables
Get exact click-by-click SPSS navigation paths for independent t-test, paired t-test, one-way ANOVA, Pearson correlation, regression, and Chi-square, plus complete APA-formatted table templates.
Chapter 06
Write, cite and format cleanly
Structure carries the reader. For most empirical papers, follow IMRaD: Introduction, Methods, Results and Discussion:
- Paraphrase honestly: Restate the idea in your own structure and still cite the source.
- Stay consistent: One citation style, applied everywhere.
- Match the template: Margins, headings, tables and figure captions.
- Write the abstract last: An abstract summarises what you actually found, so write it after the results are final.
Citation quick reference (Journal article)
| Style | Pattern |
|---|
| APA 7 | Author, A. A., & Author, B. B. (Year). Title of article. Journal Name, volume(issue), pages. https://doi.org/... |
| Vancouver | Author AA, Author BB. Title of article. Journal Abbrev. Year;volume(issue):pages. |
| IEEE | [1] A. Author and B. Author, "Title of article," Journal Abbrev., vol. x, no. x, pp. xx-xx, Year. |
| Harvard | Author, A. and Author, B. (Year) 'Title of article', Journal Name, volume(issue), pp. xx-xx. |
The Paraphrasing Test: Close the source and explain the idea from memory. Then compare: if you copied its sentence structure or key phrases, rewrite it again and cite it either way.
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Chapter-by-chapter writing checklist & style sheets
Access the detailed section-by-section breakdown (Introduction, Literature Review, Methods, Results, Discussion, Conclusion) highlighting common student mistakes and complete formatting checklists.
Chapter 07
Prepare for your viva defense
Examiners rarely try to trick you. They test whether you understand your own work:
- Why this method? Link it back to your question.
- What are the limits? Name them calmly before they do.
- What does it add? State your contribution in two clear sentences.
Answer structure: A-R-E
Answer (A): Answer directly in one sentence.
Reason (R): Give the academic or methodological reason.
Example (E): Add a concrete example from your own dataset or findings.
Stop talking, and let the examiner ask more.
The week before defense checklist
- Re-read your abstract, objectives and conclusions until you can say them without notes.
- Know every table: what it shows and why it matters.
- Time your presentation and rehearse with a colleague who asks questions.
- Prepare a calm, one-line answer to "What is your biggest limitation?"
- Arrive early and bring a printed copy with your key notes tabbed.
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Full bank of likely committee questions & mock viva prep
Unlock the comprehensive bank of committee questions across purpose, design, tools, analysis, limits, and ethics, plus book a 1-on-1 mock viva session with M. Yousaf.