Sample size and power calculator.

Plan your study with confidence. Get the sample size you need, or the power you already have, for a comparison of two means or two proportions. Your inputs never leave your browser.

Runs entirely in your browser Paste-ready methods and R code Built by a publishing physician-scientist

An underpowered study wastes everyone’s time

A study that is too small cannot find the effect it was built to find, and a reviewer will say so. A quick calculation up front protects months of work.

Justify your n

Reviewers ask for it

Ethics committees and journals expect a sample size justification. This gives you the number and the sentence to back it up.

Two designs

Means or proportions

Covers the two most common comparisons, a difference in means for a continuous outcome and a difference in proportions for a binary one.

Both directions

Size or power

Compute the sample size for a target power, or the power you already have for a fixed sample size you cannot change.

Let a named physician-scientist plan the analysis

Survival, clustered, adaptive or multi-arm designs need more than a formula. Rigora’s statistics service delivers the sample size, the protocol wording and the analysis plan, done by a publishing physician-scientist.

See statistics support Free Table 1 generator

Questions

What sample size do I need?

It depends on the effect you want to detect, the variability of your outcome, your significance level (alpha, usually 0.05 two-sided) and your target power (usually 80% or 90%). Enter those and the calculator returns the participants needed per group.

What is statistical power?

Power is the probability that your study detects a real effect of the size you specified. A study with 80% power misses a true effect one time in five, which is why underpowered studies are a common reason for non-significant results.

Does this replace a formal power analysis?

It uses the normal approximation, the standard for planning, which matches most textbooks. For the final protocol, especially for survival, clustered or adaptive designs, confirm the number with exact or simulation methods. That is part of the Rigora statistics service.

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