Type II Error

Not having enough evidence to detect that x really does influence Y. Also known as “beta (β) risk”.

A type II error, also known as a error of the second kind, is the wrong decision that is made when a test fails to reject a false null hypothesis. A type II error may be compared with a so-called false negative in other test situations. Type II error can be viewed as the error of excessive skepticism. The rate of the type II error is denoted by the Greek letter β (beta) and related to the power of a test (which equals 1 − β). What we actually call type I or type II error depends directly on the null hypothesis. Negation of the null hypothesis causes type I and type II errors to switch roles. The goal of the test is to determine if the null hypothesis can be rejected. A statistical test can either reject (prove false) or fail to reject (fail to prove false) a null hypothesis, but never prove it true (i.e., failing to reject a null hypothesis does not prove it true).