כיצד לחשב את Type I & II Errors
learn.whatIsHeading
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.
מדריך שלב אחר שלב
- 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
Worked Examples
קלט
α=0.05 · β=0.20
תוצאה
5% false positive rate · 20% false negative rate · 80% power
Standard research settings
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