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Sample size calculator

How many subjects you need, with the justification written out and ready to paste into your methods section.

Sample size is the part of the methods section that attracts most rejections and gets documented worst. Not because the arithmetic is hard, but because it has to be explained: what power, what effect size, where that effect came from and why.

This calculator does the arithmetic and, more importantly, writes the paragraph. The number alone does not convince a reviewer; the number with its justification does.

Calculate your sample size

Choose the design, enter your values and get the number, the power curve and the paragraph for your methods section. No account needed.

Study design
Cohen's conventions:
Hypothesis
Where does the effect size come from?

What it does

The designs people actually use

Two-means comparison, two proportions, correlation, one-way ANOVA, chi-square, and single-group studies estimating a proportion to a given precision.

Methods paragraph, written

Returns the full text with test, power, alpha, effect size and where it came from, in the form reviewers expect.

Power curve

Shows what happens if you recruit fewer subjects than planned, which is what ends up happening. Useful for knowing your margin in advance.

Attrition adjustment

Add the dropout rate you expect and get the number to recruit, not just the number to analyse.

Why another calculator

There are many, and several are good. None writes the justification, which is exactly the part reviewers send back. And almost all of them ask for the effect size without explaining where to get it, which is where everyone gets stuck.

Frequently asked questions

Do I need an account?

No. It is a calculator: it consumes nothing and needs no sign-up.

Where do I get the effect size?

From a similar previous study, from a pilot, or from the smallest difference you consider clinically relevant. The tool walks you through all three and records which one you used in the written paragraph.

Does it replace G*Power?

Not for complex designs. It covers the common cases and adds what G*Power does not: writing the justification.

In the meantime

This tool is available today and solves something adjacent:

Manuscript Evaluation
Sample size calculator | Explore Labs