AB Test Simulator

Interactive visualization of statistical power, effect size, and sample size relationships

Control Group (Mean: 100 min)
Treatment Group (Mean: 120 min)
Alpha (α) - Type I Error
Beta (β) - Type II Error
Power (1-β)

Effect Size (Cohen's d)

0.67
Standardized mean difference

Statistical Power (1-β)

0.80
Probability of detecting effect

Beta (β)

0.20
Type II Error Rate

Alpha (α)

0.05
Type I Error Rate

P-Value (Simulated)

0.001
From t-test simulation

📖 Understanding the Visualization

Alpha (red shaded area): The probability of rejecting the null hypothesis when it's actually true (false positive). This is shown in the right tail of the control distribution.

Beta (yellow shaded area): The probability of failing to reject the null hypothesis when the alternative is true (false negative). This is the overlap area in the treatment distribution below the critical value.

Power (green shaded area): The probability of correctly detecting an effect when it exists (1-β). This is the area in the treatment distribution above the critical value.

Effect Size: Cohen's d measures the standardized difference between groups. Larger effect sizes are easier to detect.

Try it: Increase the sample size to see how the distributions narrow, beta decreases, and power increases!