Sample Size Calculator
Calculate the minimum sample size required for a statistically valid survey or experiment. Specify confidence level, margin of error, and population size.
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How to use this calculator
n is the infinite-population sample size. n_adj applies a finite population correction when population size N is known.
- 1
Select your target confidence level (95% is the research standard).
- 2
Enter the acceptable margin of error — 5% is typical for surveys.
- 3
Leave response distribution at 50% if unknown (most conservative estimate).
- 4
Enter the population size if finite, or leave 0 for a large/unknown population.
Frequently asked questions
Why 50% response distribution?
p = 50% (0.5) gives the largest possible sample size because p(1−p) is maximised at 0.5. Using 50% is conservative and safe when you don't know the true proportion.
What is the finite population correction?
When your sample represents a large fraction of the total population, you need fewer responses than the infinite-population formula suggests. The finite correction reduces the required sample size.
Does a larger population require a larger sample?
No — once the population exceeds about 20,000, the required sample size barely changes. The margin of error is driven by the sample size, not the population fraction.
Sample Size Calculator — Survey & Research Planning
How to use the sample size
Use this sample size to he minimum sample size required for a statistically valid survey or experiment. Enter your values above and get your result in seconds. The tool is free, works on all devices, and keeps your data private — nothing is stored or shared.
How the sample size works
The sample size calculator uses standard formulas used in statistical analysis, data science, and research. Enter your inputs, and the tool calculates the result instantly in your browser. No server-side processing means your data stays on your device. Results update in real time as you change inputs.
How sample size affects accuracy
A larger sample gives a narrower margin of error and more reliable results, but the relationship is not linear. Doubling your sample size cuts the margin of error by only √2 ≈ 41%. Going from 384 to 1,537 respondents takes you from ±5% to ±2.5% at 95% confidence.
Choosing the right confidence level
95% confidence is the standard in most research and surveys. 99% confidence is used in medical and safety-critical studies where the cost of a wrong conclusion is high. 90% is acceptable for exploratory research or when resources are limited.
Sample size: how it works
Statistical analysis underpins data science, research, quality control, and business intelligence. This tool applies established textbook formulas to your dataset and returns results instantly, eliminating manual calculation errors.
Who uses this tool?
Researchers, students, analysts, and business professionals use it to understand datasets quickly. Whether you are summarising survey responses or checking experiment results, this tool delivers the key figures instantly.
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Results are estimates for informational purposes only and do not constitute professional financial, medical, legal, or technical advice. Read full disclaimer →