Calculates the statistical significance and other key metrics for A/B test results.
Start with your values, or try a preset.
Enter Control Group Impressions, Control Group Conversions, Test Group Impressions, and Test Group Conversions in the units shown.
Read Test Group Conversion Rate, Control Group Conversion Rate, and Conversion Rate Difference in the results panel. Results update as you change the inputs.
Choose a preset to load an example, then adjust the values for your situation.
See the inputs and their calculated results.
Control Group Impressions: 10,000; Control Group Conversions: 500; Test Group Impressions: 10,000; Test Group Conversions: 600
Test Group Conversion Rate: 6 %; Control Group Conversion Rate: 5 %; Conversion Rate Difference: 1 %
Control Group Impressions: 10,000; Control Group Conversions: 500; Test Group Impressions: 10,000; Test Group Conversions: 520
Test Group Conversion Rate: 5.2 %; Control Group Conversion Rate: 5 %; Conversion Rate Difference: 0.2 %
Control Group Impressions: 10,000; Control Group Conversions: 500; Test Group Impressions: 10,000; Test Group Conversions: 500
Test Group Conversion Rate: 5 %; Control Group Conversion Rate: 5 %; Conversion Rate Difference: 0 %
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Performs a t-test (one-sample, two-sample, or paired) to compare means and determine statistical significance.
Finds the Z-score corresponding to a given cumulative probability (percentile) on a normal distribution.
Calculates the Chi-Square statistic and p-value for goodness-of-fit or test of independence. It requires observed and expected frequencies or values.
Identifies potential outliers in a dataset using the IQR * 1.5 rule (calculating fences).