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🧮 P-Value Calculator

Turn a test statistic — z, t, chi-square or F — into a p-value, one-tailed or two-tailed, using exact distribution functions.

p-value

0.049996

p ≤ α — statistically significant, reject H₀

Exact p-values from the cumulative distribution functions (erf, regularized incomplete gamma & beta). 🔒 Computed in your browser.

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How the p-value calculator works

Choose the distribution your test statistic comes from, enter the statistic (and degrees of freedom for t, χ² and F), and the tool returns the p-value from the exact cumulative distribution function. For z and t you can pick a left, right, or two-tailed alternative; χ² and F tests are right-tailed. A verdict compares the p-value to your significance level (α).

The exact special functions (error function, regularized incomplete gamma and beta) are the same ones behind statistical software — so the p-value is precise, not a table approximation that a chatbot would round or get wrong.

Frequently asked questions

How do I convert a z-score to a p-value?

The p-value is the tail area beyond the statistic. For a right-tailed z-test it is P(Z > z); for two-tailed it is 2 × P(Z > |z|). Choose the distribution "z" and your tail, and the tool computes it exactly.

What is a p-value?

The probability of observing a test statistic at least as extreme as yours if the null hypothesis were true. A small p-value (typically ≤ 0.05) is evidence against the null hypothesis.

When is a result statistically significant?

When the p-value is at or below your chosen significance level α (commonly 0.05). This tool shows the verdict — reject or fail to reject the null hypothesis — against your α.

What is the difference between one-tailed and two-tailed?

A one-tailed test looks for an effect in a single direction (only larger, or only smaller); a two-tailed test looks for any difference. Two-tailed p-values are double the one-tailed value for symmetric distributions.

Which distribution should I choose?

z for large-sample or known-variance tests, t for small-sample mean tests (with degrees of freedom), χ² for goodness-of-fit and independence tests, and F for ANOVA and variance ratios.

Why not just read a table?

Tables are coarse and require interpolation; this computes the exact p-value for any statistic and degrees of freedom, with no rounding — and it runs entirely in your browser.

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