Power Analysis Visualization

Explore the relationships between Type I error, Type II error, power, and sample size

Understanding Power Analysis

• Type I Error (α): Rejecting H₀ when it's true
• Type II Error (β): Failing to reject H₀ when it's false
• Power (1-β): Correctly rejecting H₀ when it's false

Note: For meaningful results, ensure μₐ is in the direction of your alternative hypothesis!

64
66
0.05
35
3
Type I Error (α)
Type II Error (β)
Power (1-β)
Statistical Summary
Type I Error (α)
0.05
Type II Error (β)
0.478
Power (1-β)
0.522