Free A/B Test Calculator for Statistical Significance
Calculate sample size, check statistical significance, and determine how long your A/B test needs to run.
Statistical Significance Calculator
Is your A/B test winner statistically significant? Check if your results are reliable or just random chance.
Calculator
Results
Variant B vs Variant A (Control)
How to Use Our A/B Test Calculators
Get instant insights for your conversion optimization experiments
1. Enter Your Data
Input your test data including visitors and conversions for each variant, or your expected conversion rate and desired uplift.
2. Click Calculate
Our calculators instantly process your data using proven statistical formulas to give you accurate results.
3. Make Decisions
Use the results to determine if your test is significant or how long you need to run your experiment.
Understanding Statistical Significance in A/B Testing
Advanced AI-powered recommendations that deliver premium personalization—without the complexity or high costs.
What is Statistical Significance?
Statistical significance helps you determine whether the difference in conversion rates between your test variants is due to the changes you made or just random chance.
A result is statistically significant when the p-value is below your chosen significance level (we use 90% confidence, meaning p < 0.10).
This means there's only a 10% chance that the observed difference happened by random variation.
Why Sample Size Matters
Running tests with too few visitors can lead to false positives or missing real improvements. Our sample size calculator helps you avoid these pitfalls.
The required sample size depends on your baseline conversion rate, the size of improvement you want to detect, and your desired confidence level.
Testing with the right sample size ensures your results are reliable and actionable.
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