In a statistical hypothesis test, there are two types of incorrect conclusions that can be drawn. The hypothesis can be inappropriately rejected (this is called type I error), or one can inappropriately retain the hypothesis (this is called type II error). The Greek letter α is used to denote the probability of type I error, and the letter β is used to denote the probability of type II error.

Type I error is rejecting the null hypothesis when H0 is actually true. A Type II error is failing to reject the null hypothesis when alternative is actually true.

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