Evidence-appraisal glossary
Type II error
A type II error is failing to reject a null hypothesis that is actually false, that is, missing a real effect. It is a false negative.
Also called: false negative, beta error.
Its rate is written as beta, and statistical power equals one minus beta, so a study with 80 percent power carries a 20 percent chance of missing an effect of the size it was designed to detect. Type II errors are most common in small or underpowered studies, which is why a non-significant result should not be read as evidence that no effect exists.
This is a plain-language methodology definition for reading research. It is general education, not medical advice.