In null-hypothesis significance testing, the p-value is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. A very small p-value means that such an …

In statistics, every conjecture concerning the unknown probability distribution of a collection of random variables representing the observed data $${\displaystyle X}$$ in some study is called a statistical hypothesis. If we state one hypothesis only and the aim of the statistical test is to see whether this hypothesis is tenable, but not to investigate other specific hypotheses, then such a test is called a null hypothesis test. As our statistical hypothesis will, by …

DefinitionThe p-value is the probability under the null hypothesis of obtaining a real-valued test statistic at least as extreme as the one obtained. Consider an observed test-statistic $${\displaystyle t}$$ from unknown distribution $${\displaystyle T}$$. Then the p-value $${\displaystyle p}$$ is what the prior probability would be of observing a test-statistic value at least as "extreme" as $${\displaystyle t}$$ if null hypothesis $${\displaystyle H_{0}}$$ …