A/B Test Statistical Significance Calculator
Determine if your A/B test results are statistically significant with confidence intervals
About this calculator
The A/B Test Statistical Significance Calculator helps marketers and analysts determine whether their test results are statistically meaningful or just due to random chance. By calculating p-values, confidence intervals, and effect sizes, this tool ensures you make data-driven decisions about which version performs better. Whether you're testing website conversions, email campaigns, or product features, statistical significance testing prevents costly mistakes from drawing conclusions from insufficient data or random fluctuations.
How to use
Enter your test data including sample sizes, conversion rates, and desired confidence level (typically 95%). The calculator will analyze both variants and display the p-value, confidence intervals, and whether results are statistically significant. Review the effect size to understand the practical importance of any differences detected.
Frequently asked questions
What p-value indicates statistical significance?
A p-value below 0.05 (5%) is typically considered statistically significant, meaning there's less than 5% chance results occurred randomly.
How large should my sample size be?
Sample size depends on expected effect size and desired power. Generally, aim for at least 100-300 conversions per variant.
What's the difference between statistical and practical significance?
Statistical significance means results aren't due to chance, while practical significance means the difference is large enough to matter business-wise.