Sampling & recruitment: who, how many and why

Whom you study determines what you can conclude. The sample isn't a technical detail — it's the very foundation of validity.

Choose a sampling strategy deliberately

Quantitative studies often aim for representativeness (random or stratified sampling); qualitative studies aim for richness and relevance (purposive or theoretical sampling). Justify the choice from the question: who must be included for the answer to be meaningful, and whom do you risk leaving out?

Justify the size

In quantitative research a power calculation makes the sample size defensible: how many are needed to detect an effect of a given size? In qualitative research the point is saturation — when new data stop yielding new insight. Be explicit about how you determined the number.

Recruitment is where ethics and feasibility meet. Plan consent, access and privacy (Sikt/GDPR) before you approach a single participant.

Know your bias

Every sample has bias: selection, self-selection, attrition. Naming these sources and assessing how they affect your conclusions is a mark of methodological maturity — and it pre-empts the most common objection from reviewers.

Common pitfalls

• Choosing a sample from convenience without justifying it.
• Stating a sample size with no power calculation or saturation.
• Overlooking selection and attrition bias.

Ready to move on when…

• The sampling strategy is justified from the question.
• The size is defended (power or saturation).
• Sources of bias are named and assessed.