p-value

p-Value — finally understand the most misused number in statistics.

The p-value is everywhere: research papers, headlines, A/B tests, lab reports. It is also the single most misunderstood number in all of statistics. This little offline app shows you what a p-value actually is, what it is NOT, and why the famous "facts" most people repeat about it are simply wrong.

No sign-up. No internet needed. No data collected. Just clear, interactive intuition.

WHAT YOU CAN DO

• Calculate — type any test statistic (z) by hand, pick a one- or two-tailed test, and watch the p-value appear as the shaded tail area under the null curve. A plain-language sentence tells you exactly how to read it.

• Concept — see the p-value as a tail area: one- vs two-tailed, the 0.05 convention, and the crucial fact that p-values are uniform under H0. Offline KaTeX formulas, beautifully typeset.

• Dance of the p-values — run thousands of experiments and histogram their p-values. Flat when there is no real effect; piled up near zero when there is. Drag the effect size, or type it in, and watch the distribution change.

• Simulate (p-hacking) — run many tests where nothing is going on and watch about 5% turn up "significant" purely by luck. Choose 20, 40, 60, 100, or type your own number of tests.

• Examples — a worked coin example, then a side-by-side of the CORRECT vs the INCORRECT ways to state what a p-value means.

THE MYTHS, BUSTED

The p-value does NOT tell you:
• the probability that the null hypothesis is true
• the probability your result happened "by chance"
• that 1 - p is the probability the effect is real
• that a big p-value proves there is no effect

What it really tells you: IF the null hypothesis were true, how often would you see a result at least this extreme? That's it — and this app makes that idea click.

WHY YOU'LL LIKE IT

• Fully offline — every formula and chart works with no connection.
• Manual number entry — type your own test statistic, effect size, or test count.
• Tiny and fast — charts are drawn natively, so the app stays light.
• Clean "Neon Ink" design — charcoal chrome with a hot-pink tail area, cyan and lime accents.
• Privacy-friendly — your inputs stay on your device.

Whether you are a student meeting hypothesis testing for the first time, a researcher who wants a clean explainer to share, or anyone tired of seeing p-values misquoted, p-Value turns an abstract definition into something you can see, touch, and finally trust.

Download it, type in a number, and watch the tail area light up.