A/B Test Calculator
Calculate sample size and statistical significance for your A/B tests
How to Use the A/B Test Calculator
A/B testing is essential for data-driven decision making. This free calculator helps you determine the right sample size before starting your test and validate your results after collecting data.
Sample Size Calculator
Before running an A/B test, you need to know how many visitors are required to detect a meaningful difference. Enter your baseline conversion rate, the minimum effect you want to detect, your desired confidence level (typically 95%), and statistical power (typically 80%).
Statistical Significance Calculator
After your test has run, enter the number of visitors and conversions for both your control and variant groups. The calculator will tell you if the difference is statistically significant, the confidence level, the lift percentage, and the p-value.
Tips for Reliable A/B Tests
- Run your test until you reach the calculated sample size
- Don't stop the test early just because you see significant results
- Test one variable at a time for clear insights
- Ensure your traffic is randomly split between variants
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