define alpha and beta for a statistical test of hypothesesSo

define alpha and beta for a statistical test of hypotheses

Solution

Alpha is the probability of Type I error in any hypothesis test–incorrectly claiming statistical significance.

The first kind of error that is possible involves the rejection of a null hypothesis that is actually true.

This kind of error is called a type I error, and is sometimes called an error of the first kind.

Beta is the probability of Type II error in any hypothesis test–incorrectly concluding no statistical significance. (1 – Beta is power).

The other kind of error that is possible occurs when we do not reject a null hypothesis that is false. This sort of error is called a type II error, and is also referred to as an error of the second kind.