Beta (β) refers to the probability of Type II error in a statistical hypothesis test. Frequently, the power of a test, equal to 1–β rather than β itself, is referred to as a measure of quality for a hypothesis test. This entry discusses the role of β in hypothesis testing and its relationship with significance (α).
Hypothesis testing is a very important part of statistical inference: the formal process of deciding whether a particular contention (called the null hypothesis) is supported by the data, or whether a second contention (called the alternative hypothesis) is preferred. In this context, one can represent the situation in a simple 2 × 2 decision table in which the columns reflect the true (unobservable) situation and the rows ...
Looks like you do not have access to this content.