The statistical power of a binary hypothesis test is the probability that the test correctly rejects the null hypothesis ( H 0 {\displaystyle H_{0}} ) when a specific alternative hypothesis ( H 1 {\displaystyle H_{1}} ) is true. It is commonly denoted by 1 − β {\displaystyle 1-\beta } , and represents the chances of a "true positive" detection conditional on the actual existence of an effect to detect. Statistical power ranges from 0 to 1, and as the power of a test increases, the probability β {\displaystyle \beta } of making a type II error by wrongly failing to reject the null hypothesis decreases.
