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A/B Test Significance Calculator — Real Two-Proportion Z-Test
Enter your control and variant conversion numbers and this calculator runs an actual two-proportion z-test — p-value, confidence intervals, and a low-sample-size warning when your result is not yet trustworthy — rather than a rule-of-thumb "is B bigger than A" comparison. A built-in sample-size planner tells you how much traffic you need before starting. An AI pass then gives a plain-language read on whether the result is worth acting on.
How to use AI A/B Test Significance Calculator
- Enter visitors and conversions for control and variant.
- Read the p-value, confidence interval and significance verdict.
- Check the low-sample-size warning before trusting an early result.
- Use the sample-size planner for your next test.
Frequently asked questions
- What p-value counts as significant?
- Below 0.05 is the conventional threshold, meaning less than a 5% chance the observed difference is due to random variation — though the right threshold depends on how costly a false positive is for your decision.
- Why does it warn me about a "significant" early result?
- With a small sample, a z-test can report significance that will not hold up as more data arrives. The low-sample warning flags results that are still too noisy to trust.
- How is this different from a rule-of-thumb comparison?
- A rule of thumb just compares two percentages. A z-test accounts for sample size and gives you a p-value and confidence interval, so you know how much to trust the difference.
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