A/B Testing Simulation Dashboard

Interactive tool for understanding A/B testing statistics and decision-making

🎯

Conversion Rate

Website optimization

💰

Revenue per User

Monetization testing

📊

Engagement Rate

Feature adoption

🔄

Retention Rate

User retention

Control

Variant A
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Conversion Rate
-
Conversions
-
Sample Size

Treatment

Variant B
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Conversion Rate
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Conversions
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Sample Size

Experiment Parameters

1000
10%
+20%
95%
80%

Results Distribution

📚 Understanding A/B Testing

A/B testing is a method of comparing two versions to determine which performs better. The key is to ensure your results are statistically significant before making decisions.

  • Statistical Significance: The probability that the observed difference is not due to random chance
  • P-value: The probability of seeing results at least as extreme if there's no real difference
  • Power: The probability of detecting a real effect when it exists
  • Sample Size: More data = more confidence in results