Chapter Three is the part of a project that examiners read most carefully, because it shows whether your findings can be trusted. Written well, it is a recipe detailed enough that another researcher could repeat your study and get comparable results. This guide takes Nigerian undergraduate and postgraduate students through each section in the order most departments expect, with the emphasis on describing YOUR study rather than reciting textbook definitions.
The Standard Sections
- 3.1 Research Design
- 3.2 Population of the Study
- 3.3 Sample Size and Sampling Technique
- 3.4 Instrument for Data Collection
- 3.5 Validity of the Instrument
- 3.6 Reliability of the Instrument
- 3.7 Method of Data Collection
- 3.8 Method of Data Analysis
Step-by-Step
Research Design
Name your design — survey, experimental, quasi-experimental, descriptive, case study, or mixed-methods — and justify it in one or two sentences tied to your topic. Do not list every design that exists; name yours and defend why it fits your research questions.
Population and Sampling
Define your target population precisely and give its size if known. Then state your sample size and how you arrived at it. Taro Yamane is the most common formula in Nigerian undergraduate work — show the working, not just the answer. Name your sampling technique (simple random, stratified, purposive, convenience) and say why it suits your study.
Instrument, Validity and Reliability
Describe your instrument and its structure — for a questionnaire, the sections, item count and response format (e.g. a four-point Likert scale). For validity, state that your supervisor and/or subject experts reviewed it. For reliability, report your test: Cronbach's Alpha is standard for Likert questionnaires, with 0.70 or above generally accepted.
Method of Data Analysis
Match analysis to your questions. Descriptive questions use frequencies, percentages, means and standard deviations; hypotheses need an inferential test (chi-square, correlation, regression, t-test, ANOVA). Name your tool (SPSS is most common) and your significance level (usually 0.05).
Common Mistakes to Avoid
- Writing textbook definitions instead of describing your own study choices.
- A population so broad ("students in Nigeria") that it cannot be sampled meaningfully.
- Stating a sample size with no formula or working to support it.
- An analysis plan that does not map onto the research questions and hypotheses.
- Leaving the full instrument out of the appendix.
Practical Checklist
- Does each section describe my study specifically, not research in general?
- Could another student replicate my method from this chapter alone?
- Have I shown my sample-size calculation?
- Does my analysis plan cover every research question and hypothesis?
- Is my full instrument in an appendix and referenced in the text?
Example Structure (Skeleton You Adapt)
- Research design + one-line justification.
- Target population + size.
- Sample size with formula and working + named sampling technique.
- Instrument: type, sections, item count, response format.
- Validity: who reviewed and what they checked.
- Reliability: test used and the value obtained.
- Data analysis: descriptive tools, inferential tests, software, significance level.
For a deeper treatment of design and sampling, read our dedicated research methodology guide. Project Lab can help you align your method with your research questions and keep your instrument and references consistent. Next: how to write Chapter Four.
Frequently Asked Questions
Which sampling formula should I use?
Taro Yamane is the most widely accepted in Nigerian undergraduate projects because it only needs population size and a chosen error margin. Cochran's formula suits larger or more complex studies. Confirm your supervisor's preference.
What if my reliability value is below 0.70?
Report it honestly and discuss what may have caused it — ambiguous items, a small pilot, or a mixed construct. Do not alter the figure. You can note revisions you made to the instrument after the pilot.