P-Value Calculator (z, t, Chi-Square, F)

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P-Value Calculator

Enter a test statistic and this p-value calculator returns the probability of a result at least as extreme under the null hypothesis. Choose the statistic type (z, t, chi-square or F), give the degrees of freedom where needed, pick the tail and compare the p-value with your significance level.

For z and t, which are symmetric, the two-tailed p-value is twice the area beyond |statistic|. Chi-square and F statistics are almost always tested in the right tail (goodness of fit, independence, ANOVA, regression F). If you do need a two-tailed value for these, for example in an F-test of two variances, the calculator doubles the smaller tail.

The example uses t = 2.25 with 15 degrees of freedom, which gives a two-tailed p of about 0.040, significant at 0.05 but not at 0.01. To go the other way, from α to the cut-off, use the critical value calculator. To run the whole test from data, see the t-test, chi-square and ANOVA calculators.

Frequently asked questions

How do I get a p-value from a t statistic?

Choose t, enter the degrees of freedom (n − 1 for a one-sample or paired test) and the t value, then pick the tail. For a two-tailed test the p-value is 2 × P(T ≥ |t|).

What p-value is significant?

A result is called significant when p is below the significance level you chose in advance, usually 0.05. Smaller p means stronger evidence against the null hypothesis.

Is a chi-square p-value one-tailed?

Yes, in goodness-of-fit and independence tests. Large χ² values are evidence against H₀, so the p-value is the right-tail area.

What does p = 0.03 mean?

If the null hypothesis were true, a statistic at least this extreme would occur about 3% of the time. It is not the probability that the null hypothesis is true.

Last reviewed: October 7, 2026. Calculations run in your browser and were validated against SciPy.