Sample Size Calculator
Determine the ideal sample size for your surveys based on confidence level and margin of error.
Sample size determines how many people you need to survey for results you can trust. Enter your desired confidence level and margin of error below — add a population size if you're surveying a known, finite group.
Your Recommended Sample Size is
What is a Sample Size Calculator?
A sample size calculator tells you how many survey responses you need to collect for your results to reliably represent a larger population. It works by balancing four inputs:
- Confidence Level — how sure you want to be that your sample truly reflects the population. 95% is the industry standard; 99% is reserved for high-stakes decisions.
- Margin of Error — how much deviation from the true value you're willing to accept. A smaller margin gives a more precise result but requires a larger sample.
- Response Distribution — your best guess at how answers will split. Leave it at 50% if you're unsure — it's the safest, most conservative estimate.
- Population Size (optional) — the total size of the group you're surveying. Leave it blank for a large or unknown population; fill it in for a known, finite group (e.g. "all 500 employees") to reduce the required sample size via finite population correction.
Common Confidence Levels
| Confidence Level | Z-Score | Typical Use Case |
|---|---|---|
| 90% | 1.645 | Early-stage or exploratory research |
| 95% | 1.96 | Industry standard for most surveys |
| 99% | 2.576 | High-stakes decisions (medical, legal, financial) |
Note: A higher confidence level or a smaller margin of error both increase the required sample size. If you're unsure about response distribution, leave it at 50% — it produces the most conservative (largest) sample size and is guaranteed to be sufficient regardless of the true split.