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Sample Size Calculator (Free)

Free Tool

Sample Size Calculator

Estimate the sample size needed for a t-test using effect size, power, alpha, and an optional attrition buffer. This free version is built for straightforward t-test planning rather than every design under the statistical sun.

Enter your study assumptions

Choose the t-test design, enter the effect size you want to detect, and set your target power and alpha level.

What this is doing: this calculator uses a standard normal-approximation approach for t-test planning. It is useful for early design work, but it is still an estimate. Complex designs, unequal groups, clustered data, and repeated missingness need more serious handling.

Use Cohen’s d. Rough conventions are 0.20 small, 0.50 medium, 0.80 large.

0.80 is common. 0.90 is stricter and usually means a larger sample.

0.05 is the standard default in many psychology assignments.

Optional. Add this if you expect some participants to drop out or produce unusable data.

Your estimate

The result below shows the minimum analyzable sample and, if you added attrition, a more realistic recruitment target.

Analyzable sample needed
Recruitment target
Design assumed
What this means
Run the calculation to see the summary.
Check before using this number
The tool will list the main assumptions and caveats here.
See Simply Put Premium

The free version is designed for basic t-test planning. Premium is where it makes more sense to put ANOVA, correlations, broader guidance, and messier real-world designs.

What Premium does better
  • Free: straightforward t-test sample size planning
  • Premium: broader support for more designs and more detailed guidance
  • Premium: better for when the study is more complicated than two neat textbook groups

Sample Size Calculator

Estimate sample size for psychology and social science research with this free sample size calculator. Useful for study planning, dissertations, projects, and anyone trying to make more defensible decisions about power and participant numbers.

Want the stronger version?

The free tools are useful for quick fixes. If you want cleaner outputs, more control, or wider support across your work, there are two sensible ways to go.

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