Last updated October 4, 2026 · Report an error
Surveying an entire population is rarely practical — sample size calculations find the smallest sample that still produces statistically reliable results.
This calculator finds the required sample size given a confidence level, margin of error, and optional population size.
How it works
Choose a confidence level, enter your desired margin of error and expected proportion (use 50% if you have no prior estimate, since it produces the most conservative — largest — sample size), and optionally enter a finite population size. The calculator applies the standard sample size formula, with a finite population correction if a population size is given.
- Enter confidence level.
- Enter margin of error (%).
- Enter expected proportion (%, use 50 if unknown).
- Enter population size (optional).
- Click Calculate to see your results.
Examples
A standard survey
At 95% confidence and a 5% margin of error with an unknown proportion, the required sample size is 385 — a commonly cited reference figure.
Who should use it
- Planning how many survey responses to collect for a research project.
- Determining an adequate sample size for a quality control study.
Industry applications
- Market research and survey design
- Academic research and statistics
Advantages
- Supports both infinite and finite population sample size calculations.
- Shows the full formula, including the finite population correction when applicable.
Limitations
- Assumes simple random sampling — more complex sampling designs (stratified, cluster) require different formulas.
Common mistakes to avoid
- Using a very small expected proportion or a proportion far from 50% without good evidence, which can understate the required sample size if the guess turns out to be wrong.
- Ignoring the finite population correction for a small, known population, which leads to oversampling.
Best practices
- When in doubt about the expected proportion, use 50% — it's the conservative, safe default that ensures adequate sample size regardless of the true value.
Tips
- A smaller margin of error or higher confidence level both increase the required sample size — balance statistical rigor against practical data collection limits.