Another way of expressing how well a test performs is to report its power:the probability of its leading us to reject the null hypothesis when it is false.Thus, the power of a test is .• The probability of rejecting the null hypothesis when it is false.• When more than one test can be performed in a given situation, we wouldnaturally prefer to use the test that is correct more frequently.• If (given the same alternative hypothesis, sample size, and significancelevel) one test has a higher power than a second test, the first test is saidto be more powerful.