Type I and II errors (1 of 2)

There are two kinds of errors that can be made in significance testing: (1) a true null hypothesis can be incorrectly rejected and (2) a false null hypothesis can fail to be rejected. The former error is called a Type I error and the latter error is called a Type II error. These two types of errors are defined in the table.

Statistical Decision	True State of the Null Hypothesis
Statistical Decision	H₀ True	H₀ False
Reject H₀	Type I error	Correct
Do not Reject H₀	Correct	Type II error

The probability of a Type I error is designated by the Greek letter alpha (a) and is called the Type I error rate; the probability of a Type II error (the Type II error rate) is designated by the Greek letter beta (ß) . A Type II error is only an error in the sense that an opportunity to reject the null hypothesis correctly was lost. It is not an error in the sense that an incorrect conclusion was drawn since no conclusion is drawn when the null hypothesis is not rejected.