A/B Test Significance Calculator
Check whether an A/B test result is statistically significant — conversion rates, relative uplift, p-value and confidence using a two-proportion z-test.
How to use
- 1Enter visitors and conversions for version A (control) and B (variant).
- 2Pick your confidence level (95% is standard).
How it's calculated
Two-proportion z-test with pooled standard error: z = (p_B − p_A) ÷ √(p(1 − p)(1/n_A + 1/n_B)). Two-sided p-value = 2 × (1 − Φ(|z|)).
Frequently asked questions
What does 95% significance mean?
If there were truly no difference, a result this extreme would happen less than 5% of the time. It doesn't mean there's a 95% chance B is better.
Can I stop the test as soon as it's significant?
No — 'peeking' inflates false positives. Decide the sample size before the test (use the sample size calculator) and run to completion.
What if it's not significant?
You can't conclude there's no difference — the test may be underpowered. The effect might be too small to detect with this traffic.