Learn Before
Concept icon
Concept

p value

A p value is the probability, calculated under a specified statistical model, of getting a result at least as extreme as the one observed. The model combines the null hypothesis with the test's other assumptions, such as how the data were collected and how they are distributed. A p value is not the probability that the null hypothesis is true, and it is not the probability that the result occurred purely by chance. A small p value means the data would be unusual if the whole model were true; on its own it cannot say whether the null hypothesis or another assumption is at fault. By a common convention in psychology, a result is called statistically significant when p is .05 or less, that is, when p is at or below a significance level (alpha) of .05: under the model, results at least as extreme as the observed one would occur no more than 1 time in 20. A p value does not measure how large or important an effect is, and a conclusion should not rest only on whether p passes a threshold. The table below lists conventional descriptors for ranges of p; its third column shows typical but incautious interpretations that claim more than a p value can show, not correct readings.

Source: Wasserstein, R. L., & Lazar, N. A. (2016). The ASA statement on p-values: Context, process, and purpose. The American Statistician, 70(2), 129–133; section 2 and principles 1–3, 5 and 6 (pp. 131–132). https://doi.org/10.1080/00031305.2016.1154108

Image 0

0

2

Concept icon
Updated 2026-10-17

Tags

User experience (UX) research

Design Science

KPU

Research Methods in Psychology - 4th American Edition @ KPU

Related
Learn After