Sample size
Sample size is where reviewers look first, and where most proposals lose credibility. These guides explain where the numbers come from, what assumptions you are making when you use them, and how sample size works differently in qualitative studies.
Understand the formula, then calculate a number you can defend in your methods section.
- Which formula fits my design and outcome?
- What prevalence, precision and response rate should I assume?
- How many interviews are enough for a qualitative study?
Start here
Cochran's Sample Size Formula: Why Everyone Keeps Getting 384
Why Cochran's formula gives 384, how to work through each step, and when to adjust for prevalence, finite populations, non-response and clustering.
Read guideKey guides
How to Calculate Sample Size for a Cross-Sectional Study
Learn how to calculate sample size for a cross-sectional study, including prevalence, precision, finite populations, non-response and cluster designs.
8 min readProbability vs Non-Probability Sampling: Which One Fits Your Study?
Probability sampling is not always “better.” Learn when probability, purposive, convenience and other sampling approaches fit the inference your study actually needs.
7 min readSimple Random Sampling Explained With a Real Research Example
Learn what simple random sampling actually means, how to select participants correctly and why “randomly choosing whoever is available” is not random sampling.
7 min readHow Many Interviews Do You Need for a Qualitative Study? There Is No Magic Number
There is no universal rule that 12, 15 or 20 interviews is enough. Learn how to justify qualitative sample size using aim, heterogeneity, depth and information power.
7 min readSaturation in Qualitative Research: What It Means and What It Does Not Mean
“Saturation was reached after 12 interviews” is not enough. Learn the different meanings of saturation and how to document sample adequacy transparently.
10 min read
Tools and templates
See everything for this stage: what to learn, use, download and check.