P-Value Calculator

Your details

Choose Z for large samples and known variance, t for small samples with unknown variance, chi-squared for goodness-of-fit and contingency tables, and F for ANOVA or regression model comparisons.
Two-tailed tests are the safe default. Use a one-tailed test only when you committed to a direction before collecting data.
The value your test produced: a z-score, t-score, chi-square value, or F-ratio. For chi-square and F, enter a positive number.
z
The threshold at which you will reject the null hypothesis. The 0.05 level is the conventional default in most sciences.
P-valueSignificant (p < 0.05)
0.05
P-value (%)5%
One-tailed p-value0.025
0.05
p < 0.001<0.001p < 0.010.001-0.01p < 0.050.01-0.05p < 0.100.05-0.1Not significant0.1+

A z-score of 1.96 gives a two-tailed p-value of 0.0500, which is significant at alpha = 0.05.

  • The p-value is the probability of observing a test statistic at least as extreme as yours, assuming the null hypothesis is true.
  • Because p (0.0500) is below alpha (0.05), you would reject the null hypothesis at this significance level.
  • A small p-value is evidence against the null, not proof of a large or important effect. Report effect size and confidence intervals alongside the p-value.
  • Two-tailed tests count extremes in both directions and are the conservative default. Switch to one-tailed only when the direction was pre-specified.

Next stepPair this p-value with an effect size (Cohen's d, eta-squared, odds ratio, etc.) so readers can judge practical importance.

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