Survey Sample Size Calculator

About this calculator

Determining how many responses a survey needs relies on a formula built from three inputs: your desired margin of error (how much the sample result might differ from the true population value), your confidence level (typically 95%, which sets the z-score used in the calculation — 1.96 for 95% confidence), and the population size (with a finite population correction applied when the population is small relative to the sample). The core formula, n = (z² × p × (1−p)) / e², uses p = 0.5 by default because that assumption produces the most conservative — largest — required sample size when the true proportion is unknown.

This is standard methodology taught in every introductory statistics and market research course, and it's used directly by pollsters designing election surveys, UX researchers deciding how many users need to test a feature for statistically meaningful results, and market researchers sizing customer satisfaction surveys so the results can be trusted within a stated margin of error rather than being a coin flip on the actual population sentiment.

This calculator takes your target margin of error, confidence level and population size and returns the exact number of responses your survey needs to hit that precision, using the same Cochran-style formula researchers rely on.