Your p-value,
plain and simple.
Pvalr is a free p-value calculator that runs entirely in your browser. Pick a distribution, enter your test statistic, get the result. Nothing to install, nothing to sign up for.
What Pvalr does
Pvalr computes p-values for Z, T, Chi-square, and F distributions. It supports both one-tailed and two-tailed tests, lets you set a custom alpha level, and gives you a plain-English interpretation of the result. All calculations are powered by jStat, running client-side in your browser.
Four distributions
Z, T, Chi-square, and F. One-tailed and two-tailed. That covers most of what you run into in a stats course or a methods section.
Instant results
Type a number, see the p-value. No loading spinners, no API calls. Everything runs client-side with jStat.
Significance at a glance
Set your alpha level and Pvalr tells you whether the result clears the bar. The verdict is right there, no mental math required.
Nothing leaves your device
All computation happens in the browser. Your test statistics are not sent anywhere, stored anywhere, or logged anywhere.
Built for students and researchers
Pvalr is aimed at undergrad students taking their first statistics course and early-career researchers who just need a quick answer. If you are working through a problem set, reviewing a paper, or double-checking output from R or SPSS, this is a fast way to confirm a p-value without opening another application. It is also useful when you need to look up whether 2.31 is significant at alpha = 0.05 with 14 degrees of freedom and do not want to dig through a table.
Why “Pvalr”?
“P-val” plus “r” as a nod to the R programming language, which is common in statistics. Short, easy to type into a URL bar, and clear enough that you know what it does before you get there.
No accounts. No data collection.
Pvalr is free and ad-supported. There are no sign-ups and no email captures. We use PostHog for anonymous page-view analytics and that is it. Full details in the Privacy Policy.
For educational use. A low p-value means the result would be unlikely under the null hypothesis. It does not measure effect size or practical importance. Interpret results in context and consult a statistician for high-stakes decisions.