RESEARCH · METHODS · EVIDENCE
P-values and interpretation
Browse statistics lessons
- Statistics for research
- Center and spread
- Distributions and standard errors
- Statistical inference
- P-values and interpretation
- Critical values and test direction
- Compare means with t-tests
- Read t-test output
- Compare several means with ANOVA
- Read an ANOVA table
- Analyze categorical counts
- Read chi-square output
- Describe an association
- Read correlation results
- Interpret a regression model
- Choose a statistical method
- Statistics resources
A p-value describes how unusual the observed or more extreme results would be under the specified null model and its assumptions. It is not the probability that the null hypothesis is true, that a result occurred by chance alone, or that the finding will replicate.
If a threshold is used, specify it in the analysis plan. Do not base conclusions only on crossing it. Report effect sizes, confidence intervals, design limitations, and the number of analyses. Statistical significance does not establish practical importance; non-significance does not demonstrate no effect.
References: ASA statement on p-values