Statistics

Sample Size Calculator

Estimate required sample size from confidence level, margin error, and proportion.

Last validated: 2026-02-14

Sample Size Calculator estimates required sample size from effect size, confidence, and power assumptions. It is useful for experiment planning and survey design before data collection starts. The tool helps avoid underpowered studies and unnecessary oversampling. Use it to justify data requirements in planning documents.

Permalink

Input Pattern

Enter values in the left panel, keep units explicit, run the calculation, then copy or share the result. Invalid fields are highlighted immediately.

Sample Size Inputs

Result

Infinite population n: 385

Adjusted n: 385

How to use this tool

Enter expected effect size, confidence level, and desired power.
Run the calculator to estimate minimum sample size.
Adjust assumptions to see how design choices change required n.

Worked Example

Auto-generated from the tool's current default or entered inputs.

Example Inputs

Confidence: 95
Margin error percent: 5.0
Estimated proportion percent: 50.0
Population size: 0
Sample size infinite: 385
Sample size adjusted: 385

Expected Outputs

Margin error percent: 5
Estimated proportion percent: 50
Population size: 0
Sample size infinite: 385

Interpretation

Margin error percent is 5.0. Use this as a decision input, not as a standalone conclusion.
Estimated proportion percent is 50.0. Use this as a decision input, not as a standalone conclusion.
Population size is 0. Use this as a decision input, not as a standalone conclusion.
Interpret this value alongside sample quality and assumptions to avoid overconfidence.

Scenario Compare (A vs B)

Use this to compare two input sets and quantify change in key outputs.

Scenario A

Confidence

Margin error percent

Estimated proportion percent

Population size

Sample size infinite

Sample size adjusted

Scenario B

Confidence

Margin error percent

Estimated proportion percent

Population size

Sample size infinite

Sample size adjusted

Confidence and limitations

Outputs are deterministic formula results and depend entirely on input quality and units.
Results are for planning and learning; verify with domain standards before safety-critical use.
Interpretation depends on assumptions (distribution, independence, sample quality).

Formula References

Frequentist estimation and hypothesis-test formulas used in standard textbooks.
Interpretation depends on sample quality and assumptions.

Assumptions

Outputs are deterministic formula results and depend entirely on input quality and units.
Results are for planning and learning; verify with domain standards before safety-critical use.
Interpretation depends on assumptions (distribution, independence, sample quality).

Explore more versions

Tailored guides for specific audiences, regions, and scenarios.

core