<Dd> The test's probability of correctly rejecting the null hypothesis . The complement of the false negative rate, β. Power is termed sensitivity in biostatistics . ("This is a sensitive test . Because the result is negative, we can confidently say that the patient does not have the condition .") See sensitivity and specificity and Type I and type II errors for exhaustive definitions . </Dd> <Dd> For simple hypotheses, this is the test's probability of incorrectly rejecting the null hypothesis . The false positive rate . For composite hypotheses this is the supremum of the probability of rejecting the null hypothesis over all cases covered by the null hypothesis . The complement of the false positive rate is termed specificity in biostatistics . ("This is a specific test . Because the result is positive, we can confidently say that the patient has the condition .") See sensitivity and specificity and Type I and type II errors for exhaustive definitions . </Dd> <Dt> Significance level of a test (α) </Dt> <Dd> It is the upper bound imposed on the size of a test . Its value is chosen by the statistician prior to looking at the data or choosing any particular test to be used . It is the maximum exposure to erroneously rejecting H he / she is ready to accept . Testing H at significance level α means testing H with a test whose size does not exceed α . In most cases, one uses tests whose size is equal to the significance level . </Dd>

What is a procedure that tests a hypothesis