Show pageBacklinksCite current pageExport to PDFBack to top This page is read only. You can view the source, but not change it. Ask your administrator if you think this is wrong. The power of a binary hypothesis test is the probability that the test correctly rejects the null hypothesis (H0) when a specific alternative hypothesis (H1) is true. The statistical power ranges from 0 to 1, and as statistical power increases, the probability of making a type 2 error decreases. For a type 2 error probability of β, the corresponding statistical power is 1-β. For example, if experiment 1 has a statistical power of 0.7, and experiment 2 has a statistical power of 0.95, then there is a stronger probability that experiment 1 had a type 2 error than experiment 2, and experiment 2 is more reliable than experiment 1 due to the reduction in probability of a type 2 error. It can be equivalently thought of as the probability of accepting the alternative hypothesis (H1) when it is true—that is, the ability of a test to detect a specific effect, if that specific effect actually exists. Usually set as 20%. statistical_power.txt Last modified: 2024/06/07 02:50by 127.0.0.1