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Get the p-value for a z, t, or chi-square test statistic, one- or two-tailed, and see whether it's significant at your chosen α.
Also covers: P-value from t · P-value from z · P-value from chi-square · Significance calculator
P-value
0.03573
Significant at α = 0.05: reject the null hypothesis.
The p-value is the probability of a result at least this extreme if the null hypothesis were true. It is not the probability that the null hypothesis is true.
z for tests on large samples or known σ, t for means with an estimated SD, chi-square for goodness-of-fit and independence tests.
Type the test statistic from your calculation or software output, plus the degrees of freedom for t and chi-square.
Two-tailed tests whether there's any difference; one-tailed tests a stated direction. The result says whether it's significant at your α.
Use two-tailed unless you decided on a direction before seeing the data, e.g. "the new method scores higher". A one-tailed p-value is half the two-tailed one, so choosing it afterwards overstates the evidence.
If the null hypothesis were true, a result at least this extreme would happen less than 5% of the time. It doesn't tell you the size or importance of an effect; report an effect size too.
The t and chi-square distributions come from jStat, and the normal distribution is accurate to about 7 significant digits, which is more than enough for reporting p-values.
No. Every calculation runs in your browser, and nothing you enter is sent to a server.
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