Sample Size Calculator
Find how many people you need to survey to estimate a proportion within a chosen margin of error and confidence level, with an optional finite-population correction.
- z-score
- 1.9600
- Unrounded
- 384.15
Survey at least 385 people to estimate the proportion within your margin of error at this confidence level.
How to use this calculator
- Choose your confidence level — how sure you want to be (95% is standard).
- Set the margin of error — how close your estimate should be to the true value (e.g. ±5%).
- Set the expected response distribution (use 50% if unsure — it gives the largest, safest sample).
- Optionally enter the total population size for a finite-population correction.
Sample size formula
For a proportion with a large population, the required sample size is:
where z is the z-score for your confidence level, p is the expected proportion, and E is the margin of error. For a finite population of size N, the result is adjusted downward with the finite-population correction.
Why 50% is the safe default
The term p(1 − p) is largest when p = 0.5. If you don’t know the expected proportion in advance, using 50% gives the maximum required sample size, so your survey will be large enough no matter how responses actually split.
Frequently asked questions
What sample size do I need for a 95% confidence level and 5% margin of error?
For a large population with a 50% response distribution, you need about 385 respondents for a 95% confidence level and a ±5% margin of error.
Does a larger population need a larger sample?
Only up to a point. Beyond a few thousand people, the required sample size barely changes — which is why national polls often survey around 1,000–1,500 people.
What response distribution should I use?
If you have no prior estimate, use 50%. It maximizes the required sample size and guarantees your survey is large enough regardless of how responses split.