Type II Error (β)
Failing to reject H₀ when it is actually false — a real effect is missed.
Also known as: Type II error, false negative, beta error
A Type II error (β error, false negative) occurs when a test fails to declare an effect that actually exists. Its probability β depends on effect size, dispersion, sample size, and α.
- Power = 1 − β — probability of finding a real effect (see power)
- Common target: β ≤ 0.20 (power ≥ 0.80)
- Costs often invisible — the missed effect simply stays undetected, no alarm is raised
See also
Used in
Sources
- Neyman, J. & Pearson, E. S. — On the Problem of the Most Efficient Tests, 1933
- Cohen, J. — Statistical Power Analysis for the Behavioral Sciences, 2nd Edition, Erlbaum