Deciding and Justifying Your Sample Size
"How many participants do I need?" is one of the most common questions students ask, and "Why this number?" is one of the most common questions examiners ask. There is no single correct answer, but there are accepted ways to decide and justify a sample size. In this blog, we'll look at the main approaches for quantitative and qualitative studies.
Why Sample Size Matters:
- In quantitative research, too small a sample may fail to detect real effects, while an unnecessarily large one wastes time and resources.
- In qualitative research, the aim is enough depth to answer your question, not statistical representativeness.
- In both cases, a clear justification shows that your decision was planned, not arbitrary.
Power Analysis for Quantitative Studies:
- A power analysis estimates the sample size needed to detect an effect of a given size.
- You need to decide the expected effect size, the significance level (commonly 0.05) and the desired power (commonly 0.80).
- Free software such as G*Power can carry out the calculation for many common tests, including t-tests, ANOVA, correlation and regression.
- Base your expected effect size on previous studies or a pilot study where possible, and report where it came from.
Other Quantitative Approaches:
- For surveys that estimate a population proportion, formulas such as Cochran's formula or published tables, such as Krejcie and Morgan's, are often used.
- Some analysis methods, such as factor analysis and structural equation modelling, have their own sample size guidance. Check the methodological literature for the technique you plan to use.
- Allow for non-response by inviting more people than your target sample.
Sample Size in Qualitative Research:
- Many qualitative studies use the idea of saturation: collecting data until new interviews add little new information.
- The appropriate number depends on your approach, the complexity of your topic and how similar your participants are.
- Justify your number by referring to your approach, relevant methodological guidance and, if applicable, when you judged saturation was reached.
How to Write the Justification:
- State your target sample size and your achieved sample size.
- Explain how you arrived at the target, including any power analysis inputs or saturation criteria.
- Cite the sources you relied on, and discuss any shortfall in your limitations section.
A good sample size is one you can explain and defend. Use power analysis or accepted formulas for quantitative work, use saturation and methodological guidance for qualitative work, and report your reasoning clearly. Your examiners will be far more convinced by a clear rationale than by a large number alone.