what is a type ii error accepting a false null hypothesis
In statistical hypothesis testing, a type I error is the incorrect rejection of a true null hypothesis (a false positive), while a type II error is the failure to reject a false null hypothesis (a false negative).he rate of the type II error is denoted by the Greek letter Î² (beta) and related to the power of a test (which equals 1âÎ²). 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.