P-value that had only 6 cups been presented (3 of each), a perfect classification would have only yielded a "p"-value of formula_38 which would not have met this level of significance. Fisher also underlined the interpretation of "p," as the long-run proportion of values at least as extreme as the data, assuming the null hypothesis is true. In later editions, Fisher explicitly contrasted the use of the "p"-value for statistical inference in science with the Neyman–Pearson method, which he terms "Acceptance Procedures". Fisher emphasizes that while fixed levels such as 5%, 2%, and 1% are convenient, the exact "p"-value can be
P-value AMA style uses ""P" value," APA style uses ""p" value," and the American Statistical Association uses ""p"-value." In statistics, every conjecture concerning the unknown distribution formula_1 of a random variable formula_2 is called a "statistical hypothesis". If we state one hypothesis only and the aim of the statistical test is to verify whether this hypothesis is not false, but not, at the same time, to investigate other hypotheses, then such a test is called a "significance test". A statistical hypothesis that refers only to the numerical values of unknown parameters of a distribution is called a "parametric hypothesis". Methods of