How many people should you survey? M&E sample size calculator
Nov 09 2026 · Method
How many people to survey, why, and the free calculator — with the assumptions stated plainly.
For a survey estimating a proportion, a sample of about 384 gives ±5% at 95% confidence for a large population; smaller populations need fewer (≈278 for 1,000, ≈169 for 300). The calculation depends on three assumptions: the confidence level (usually 95%), the margin of error (usually 5%), and the expected proportion (0.5 is the safe default). For cluster designs, multiply by the design effect. Adjust for non-response by dividing by the expected response rate. State all assumptions in your methods section — an unexplained sample size is the first thing an evaluator questions.
What is the basic sample size formula for a survey?
The formula for estimating a proportion is n = (Z^2 × p × (1-p)) / e^2, where Z is the Z-score for your confidence level, p is the expected proportion, and e is the margin of error. For a 95% confidence level and a 5% margin of error, with p = 0.5, this gives about 384. This assumes a large population and simple random sampling.
How does population size affect the sample size?
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Written for M&E professionals. Not a guarantee of accuracy — always verify every claim against its source, and let a named human sign off. Get the free handbook.