A type II error is a statistical term referring to accepting a false null hypothesis. It contrasts with a type I error that occurs when rejecting a true null hypothesis.

P-value is the level of marginal significance within a statistical hypothesis test, representing the probability of the occurrence of a given event.

First, a hypothesis statement and assumption are made about the population parameter or probability distribution. This initial statement is called the Null Hypothesis and is denoted by Ho. An ...

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Expanding on earlier work [especially Edwards, Lindman, and Savage (1963) and Dickey (1977)], it is shown that actual evidence against a null (as measured, say, by posterior probability or comparative ...

And again, an important characteristic of hypothesis testing is that statisticians can only attach a probability about being wrong if they reject the null hypothesis.

Robert E. Bechhofer, Salah Elmaghraby, Norman Morse, A Single-Sample Multiple-Decision Procedure for Selecting the Multinomial Event Which Has the Highest Probability, The Annals of Mathematical ...