When H1 is valid, according to the test level α, the probability that the hypothesis test can reject H0 is called the test efficacy, which is often expressed by the symbol 1-β. Factors affecting test efficacy are: test level α, the size of the difference between the overall corresponding to H0 and H1, the overall standard deviation δ, the sample size n.

Test level α: when the sample size n is certain, α decreases, β increases, the test efficacy at this time decreases; α increases, β decreases, the test efficacy at this time increases

The size of the difference between H0 and H1 corresponding to the overall corresponding to the overall parameters of the overall corresponding to H0 and H1, respectively, the greater the test efficacy. H0 and H1: the larger the difference between the different overall parameters corresponding to H0 and H1, respectively, the greater the test efficacy, and vice versa, the test efficacy decreases

Overall standard deviation δ: the smaller δ is, the smaller the degree of dispersion of the data is, the data is concentrated, and the greater the test efficacy is at this time Sample size n: as the sample size increases, the degree of dispersion of the data decreases, the data is more centralized, and the test efficacy is increased at this time