A/B Test Significance Calculator

Determine if your A/B test results are statistically significant. Make data-driven decisions with confidence.

Test Data
Enter your A/B test results to calculate significance

Variant A (Control)

Variant B (Treatment)

Higher confidence reduces chance of false positives

Results
Statistical significance analysis

Enter your A/B test data to see the significance analysis

Understanding A/B Test Significance

Key Concepts:

  • P-Value: Probability results occurred by chance
  • Z-Score: How many standard deviations from the mean
  • Confidence Level: How certain you want to be
  • Statistical Power: Ability to detect true differences

Best Practices:

  • • Run tests for at least 1-2 weeks
  • • Ensure adequate sample sizes
  • • Test one variable at a time
  • • Don't stop tests early based on results

Remember: Statistical significance doesn't guarantee practical significance. Consider business impact, implementation costs, and long-term effects when making decisions.