Statistics / Tests
P-Value Calculator (from z, t, χ², or F)
Find the p-value for a test statistic from the normal, Student's t, chi-square, or F distribution, with the degrees of freedom, as two-sided and one-sided values where they apply.
P-Value Calculator (from z, t, χ², or F): The p-value is the area of the distribution beyond the statistic. For z and t it is computed for both tails and each tail separately; for χ² and F, which test variances and fit, the right tail. The distributions are computed with the incomplete gamma and beta functions and agree with SciPy: z = 1.96 gives p = 0.0500 two-sided, and χ² = 3.84 with 1 degree of freedom p = 0.0500. Runs 100% locally in your browser with zero server file uploads.
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The p-value is the probability of a statistic at least this extreme if the null hypothesis were true. For z and t, the two-sided value counts both tails; use a one-sided value only if the direction was decided before seeing the data. χ² and F tests use the right tail. The distributions are computed in the browser and match statistical software to many decimal places.
Critical values
Two-sided 5% critical values: z = 1.96; t = 2.228 with 10 degrees of freedom and 2.042 with 30; χ² = 3.84 with 1 degree of freedom and 5.99 with 2; F = 3.49 with 2 and 20.
To run the whole test from data, use the t-test calculator or the chi-square calculator.
Small p-values
Very small p-values are shown as < 0.0001; at that point the exact figure says little more. With large samples even trivial differences give small p-values.
The z-score calculator shows the same normal tails on a curve.
How to use it
- Choose the distribution: z, t, χ², or F.
- Enter the statistic and its degrees of freedom.
- Read the two-sided and one-sided p-values, or the right-tail p for χ² and F.
Privacy & limitations
Everything is calculated in your browser.
Related tools
Frequently asked questions
One-sided or two-sided?
Two-sided unless you decided before seeing the data that only one direction mattered; a one-sided p is half the two-sided one.
Is p < 0.05 proof of an effect?
No: it means data this extreme would be unusual if there were no effect. Report the effect size and confidence interval too.
Where do I find the degrees of freedom?
For a one-sample t-test, n − 1; for a χ² table, (rows − 1) × (columns − 1); for one-way ANOVA, k − 1 and N − k.
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