A/B Test Significance Calculator
Check if your A/B test results are statistically significant. Enter data from both variations to get instant p-value analysis.
Control (A) — Original Version
Variant (B) — New Version
Formula
What is Statistical Significance?
Statistical significance tells you whether the difference between your A/B test variations is real or just random noise. A result is statistically significant at the 95% level when the p-value is below 0.05 — meaning there's less than a 5% chance the difference happened by coincidence.
This calculator uses a two-proportion z-test to compare conversion rates between your control (A) and variant (B), giving you an instant p-value and confidence level.
How to Interpret Your Results
- p-value < 0.05: Statistically significant — you can confidently deploy the winner
- p-value 0.05–0.10: Marginally significant — consider running the test longer
- p-value > 0.10: Not significant — the difference is likely due to random chance
Important: Statistical significance doesn't mean the result is practically significant. A 0.1% lift might be statistically significant with a huge sample but not worth implementing.