P-Value Calculator
A p-value is the probability of obtaining a test result at least as extreme as the observed result, assuming the null hypothesis is true. A small p-value (typically < 0.05) suggests the result is unlikely due to chance alone.
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Tip: P-values do NOT measure the size of an effect or its practical importance. A tiny, unimportant effect can have p < 0.001 with a large enough sample. Always report effect sizes too.
- 1State your null hypothesis (H₀) — usually "no effect" or "no difference"
- 2Calculate the test statistic (Z-score, t-score, etc.)
- 3Look up the p-value from the appropriate distribution
- 4If p < α (significance level), reject H₀
Z = 2.0, two-tailed=p = 0.0455Significant at α = 0.05 (p < 0.05)
Z = 1.5, two-tailed=p = 0.1336Not significant at α = 0.05
| P-value | Significance | Interpretation |
|---|---|---|
| p < 0.001 | *** | Highly significant |
| p < 0.01 | ** | Very significant |
| p < 0.05 | * | Significant (conventional threshold) |
| p < 0.10 | † | Marginally significant (some fields) |
| p ≥ 0.10 | n.s. | Not significant |
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Fun Fact
The p < 0.05 threshold was proposed by Ronald Fisher in 1925 almost arbitrarily — he suggested it as a convenient rule of thumb, not as a definitive standard. It has since been criticized as causing a reproducibility crisis in science.
References
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