Type II error

In statistical hypothesis testing, a Type II error consists of failing to reject an invalid null hypothesis (i.e. falsely accepting an invalid hypothesis).

The symbol for the probability of a Type II error is <math>\beta<math> (beta). The power of a statistical test is defined as <math>1 – \beta<math>. A test with high sensitivity will have fewer Type II errors. However, as the likelihood of Type II error decreases, the likelihood of Type I error increases.

See also

• Type I error
• Type III error