A/B Test Statistical Significance Calculator
Calculate the statistical significance, uplift and winning variant of your A/B test using the chi-squared test.
A/B Test and Statistical Significance Calculation
The A/B test calculator measures the performance of changes in your marketing campaigns or website (button color, headline, image, etc.) with scientific data. It verifies whether the difference in conversion rates between two variations is due to chance or the change made, using the Statistical Significance test.
How to Interpret A/B Test Results?
Two key metrics stand out when evaluating test results: Conversion Rate and Confidence Level. If one version outperforms the other at 95% or higher confidence, the result is considered 'significant' and the change can be made permanent.
P-Value and Significance Level
In statistical analysis, the p-value indicates the probability that the observed difference is entirely due to chance. Typically, a p-value below 0.05 is required. The lower this value, the more definitive and reliable the difference between variations A and B.
Why Does Sample Size Matter?
An A/B test must reach a sufficient number of users (traffic) to produce accurate results. Tests conducted with too little data can be misleading. Our calculator analyzes how free from 'noise' the result is based on the sample size you enter.