Sample Size Calculator β€” survey sample size

Find how many survey responses you need from confidence level, margin of error and population size, with finite-population correction.

πŸ”’ Runs entirely in your browser. Your input and output are never sent to a server or stored β€” fully private.

Formula: nβ‚€ = zΒ²Β·p(1βˆ’p)/eΒ², with finite-population correction n = nβ‚€/(1+(nβ‚€βˆ’1)/N) when a population size is given. 50% distribution is the safest (largest) choice. Click a result to copy.

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About this tool

This sample size calculator tells you how many survey responses you need for a result you can trust. Choose a confidence level (usually 95%), the margin of error you can live with (say Β±5%), the expected response split (50% is the safe default) and, if your group is small, the total population. It applies Cochran's formula with the finite-population correction and shows the required sample, plus a quick table for tighter or looser margins. It runs entirely in your browser β€” no data, no sign-up.

Frequently asked questions

Why default the response distribution to 50%?

Because 50/50 is the most cautious assumption β€” it produces the largest required sample. The formula uses p Γ— (1 βˆ’ p), which peaks at p = 0.5, so if you have no prior idea how people will answer, 50% guarantees your sample is big enough whatever the true split turns out to be. If you genuinely expect a lopsided result (say 90/10 from past data), entering that lets you get away with a smaller sample.

What does the finite-population correction do?

For a huge population, the required sample barely depends on the total β€” polling a whole country or a whole city needs about the same number. But when your population is small (a class, a company, a club), you do not need as many responses, and the correction shrinks the requirement accordingly. For example Β±5% at 95% needs about 385 responses from a very large group, but only around 278 if the whole population is 1,000.

Is this all computed locally?

Yes β€” the whole calculation is JavaScript in your browser, so nothing you enter is uploaded, and it works offline once loaded. One caveat the number can't capture: it assumes a random, representative sample. If your respondents self-select or you can't reach part of the population, no sample size fixes that bias β€” coverage and randomness matter as much as raw numbers.