P-Value Calculator

The p-value is the probability of seeing a test statistic as extreme as yours, assuming the null hypothesis is true. A small p-value means the result would be very unlikely by chance alone, which is evidence against the null hypothesis. It is not the probability that your hypothesis is true.

By convention, a p-value below 0.05 (5%) is called statistically significant, and below 0.01 is highly significant. That cutoff means a false alarm rate of 1 in 20 if the null hypothesis is true. The calculator compares your p-value with these thresholds automatically, but you should decide the significance level before collecting data.

A two-tailed test checks for a difference in either direction — for example, whether a new teaching method changes scores at all. A one-tailed test checks a specific direction, like improvement only. For the same statistic, the two-tailed p-value is exactly double the one-tailed value, so switching tails can change a borderline conclusion.

Select the z option and enter your z-score. For a two-tailed test, the calculator computes 2 × (1 − Φ(|z|)), where Φ is the standard normal cumulative function. For example, z = 1.96 gives a two-tailed p-value of 0.05 exactly — the classic threshold used across Indian research studies and journals.

For t-scores and chi-square statistics you also need the degrees of freedom. For a t-test with 10 degrees of freedom and t = 2.228, the two-tailed p-value is 0.05. For a chi-square test with 1 degree of freedom and a statistic of 3.8415, the p-value is also 0.05 — both match the printed statistical tables.