Type II error
A Type II error is failing to reject a false null hypothesis: a false negative, missing a real effect that is actually present.
A Type II error is a miss, the mistake of overlooking an effect that truly exists. Its probability is written (the Greek letter beta), and the power of the test equals , the chance of catching a real effect. For example, acquitting a guilty defendant is a Type II error when the null hypothesis of innocence is false. Larger samples and bigger true effects lower , cutting the risk of a Type II error.
More hypothesis testing terms, or browse the full statistics glossary.