P-value calculator
A p-value from your test statistic, with both tails shown and no badge saying “significant” — because that word turns a continuous measure of surprise into a yes or a no, and the conversion is where the damage happens. Nothing you type here leaves your browser — it is worked out on your own device, so there is nothing to send and nothing to log.
Before the number. A p-value is not the probability that your hypothesis is true. It is not the probability the result happened by chance. It is not a measure of how big or important the effect is. It is the probability of seeing data at least this extreme if there were no effect at all — and that is a narrower statement than almost everybody takes it for.
What a p-value is, exactly
It is the probability of getting data at least as extreme as yours if the null hypothesis were true. That is the whole definition, and every common misreading comes from dropping the conditional clause at the end.
It is not the probability that your hypothesis is true. It is not the probability that the result was chance. It is not one minus the probability that you are right. Those are all statements about the hypothesis given the data, and a p-value is a statement about the data given the hypothesis. They are different quantities and swapping them is the single most common error in applied statistics.
Why this page will not say “significant”
Because the word does the damage. A p-value is a continuous measure of how surprising your data would be under the null — 0.049 and 0.051 are indistinguishable as evidence — and calling one of them significant and the other not converts that continuum into a yes or a no.
The American Statistical Association published a statement in 2016 specifically about this. This page gives you the number and the threshold you chose, and describes where one sits relative to the other. What that means is your judgement, not ours.
One tail or two, decided in advance
A one-tailed p-value is half the two-tailed one. That means anybody who looks at their data first and then picks the tail has approximately doubled their chance of landing under any threshold they like.
This page always shows you both, so the choice is visible rather than buried. Decide which question you are asking before you look.
And it says nothing about size
A difference far too small to care about will produce an arbitrarily small p-value if you measure enough people. A large and important difference will produce an unimpressive one if you measure six.
The p-value answers “could this plausibly be nothing?” It does not answer “is this big enough to matter?”, and that second question is usually the one you actually had.