Minimum Detectable Effect (MDE) Calculator

Delivering Growth

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Calculator Configuration

Baseline Conversion Rate (%)

Sample Size Per Variant

Confidence Level

95%

90%99%

Statistical Power

80%

60%95%

Recommended: For a more comprehensive calculator that combines sample size, duration estimation, and comparison tables, check out our Sample Size and Test Duration Calculator.

How it works

What is MDE?

MDE is the smallest effect your experiment can reliably detect given a specific sample size, baseline rate, and statistical power.

Calculating MDE Given a Sample Size

If we know our sample size we can use that to see what MDE we could detect.

For example we might determine that we can afford to run an A/B test for 2 weeks and can calculate how many visitors we'd get in those two weeks.

The Formula

We calculate MDE using the formula:

\text{MDE} = \frac{(Z_{\alpha} + Z_{\beta}) \cdot \sqrt{2 \cdot p \cdot (1 - p)}}{\sqrt{n}}

Where:

p is the baseline conversion rate
n is the sample size per variant
$Z_{\alpha}$ is the Z-score for your confidence level (e.g. 1.96 for 95%)
$Z_{\beta}$ is the Z-score for your desired power (e.g. 0.84 for 80%)

Community

Need help implementing experiments?

Turn insights from this simulator or calculator into real results. The Delivering Growth Community (free to join) helps PMs, engineers, and founders build experimentation systems that drive conversion, activation, and retention. You'll learn to do this without bloated tooling or siloed teams.

✅ Guidance on A/B testing infrastructure and reliable experiments
✅ Code templates and patterns from top Growth teams
✅ Community of growth practitioners sharing wins and strategies