Margin of Error Calculator
Calculate the margin of error for your survey results based on sample size and confidence level.
Margin of error tells you how much your survey results might differ from the true opinion of the whole population. Enter your sample size and confidence level below — add a population size if you're surveying a known, finite group.
Your Margin of Error is
What is Margin of Error?
Margin of error is the range around your survey result within which the true population value likely falls. A result of 60% with a ±4% margin of error means the real figure is probably somewhere between 56% and 64%. It's driven by four inputs:
- Confidence Level — how sure you want to be that the true value falls within your margin of error. 95% is the industry standard; 99% is reserved for high-stakes decisions.
- Sample Size — how many people responded to your survey. Larger samples produce a smaller, more precise margin of error.
- 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 apply a finite population correction, which shrinks the margin of error.
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 larger sample size or a lower confidence level both shrink the margin of error. If you're unsure about response distribution, leave it at 50% — it produces the most conservative (largest) margin of error, so your real result will be at least as precise as reported.