📊F-test (Variance Ratio)
Type I error (α) is rejecting a true null hypothesis (false positive). Type II error (β) is failing to reject a false null hypothesis (false negative). Power = 1−β. Reducing α increases β.
- 1Type I rate = α (significance level, typically 0.05)
- 2Type II rate = β (typically 0.20 for 80% power)
- 3Larger sample size reduces both error types simultaneously
α=0.05 · β=0.20=5% false positive rate · 20% false negative rate · 80% powerStandard research settings
| H₀ True | H₀ False | |
|---|---|---|
| Reject H₀ | Type I error (α) | Correct (Power) |
| Fail to reject | Correct (1-α) | Type II error (β) |
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Fun Fact
In drug trials, Type II errors can be more dangerous — missing a real treatment effect means patients miss effective therapy.
References
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