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P-Value


A P-value is the probability, under a specified null hypothesis and its statistical model, of obtaining a test statistic at least as extreme as the observed value. The meaning of extreme is fixed by the test and its alternative hypothesis (Orloff and Bloom 2022, pp. 1-4). For a random variable T representing the test statistic, with observed value t, an upper-tailed test uses

 p=P_0(T>=t),
(1)

where P_0 denotes probability calculated under the null hypothesis. A lower-tailed test uses

 p=P_0(T<=t).
(2)

For a symmetric null distribution centered at 0, a conventional two-sided test uses

 p=P_0(|T|>=|t|).
(3)

Thus a P-value need not be an upper-tail probability. It does not give the probability that the null hypothesis itself is true (Wasserstein and Lazar 2016, p. 131).


See also

Alpha Value, Hypothesis Testing, Significance, Significance Level, Tail Probability

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References

Orloff, J. and Bloom, J. "Null Hypothesis Significance Testing II." Class 18 in 18.05 Introduction to Probability and Statistics. Cambridge, MA: Massachusetts Institute of Technology, Spring 2022. https://ocw.mit.edu/courses/18-05-introduction-to-probability-and-statistics-spring-2022/mit18_05_s22_class18-prep.pdf.Wasserstein, R. L. and Lazar, N. A. "The ASA's Statement on p-Values: Context, Process, and Purpose." Amer. Statist. 70, 129-133, 2016. https://doi.org/10.1080/00031305.2016.1154108.

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P-Value

Cite this as:

Weisstein, Eric W. "P-Value." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/P-Value.html

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