P Value Calculator
Compute two-tailed P values from Z, t, F, Pearson r, or Chi-square statistics. Instant results — no sign-up needed.
P Value Significance Reference
Use the table below to interpret your P value against standard significance thresholds.
| P value range | Significance level | Interpretation |
|---|---|---|
| P < 0.001 | α = 0.001 (***) | Extremely significant |
| P < 0.01 | α = 0.01 (**) | Highly significant |
| P < 0.05 | α = 0.05 (*) | Statistically significant |
| P ≥ 0.05 | n.s. | Not statistically significant |
How This Calculator Works
All computations run entirely in your browser using high-precision JavaScript implementations of the following distributions:
Z (standard normal): Two-tailed P = 2 × (1 − Φ(|Z|)), where Φ is the normal CDF approximated via the complementary error function (erfc) with 7-coefficient Horner polynomial — accurate to better than 1.5 × 10⁻⁷.
t (Student's t): Uses the regularized incomplete beta function Ix(a, b) via Lentz's continued fraction algorithm. Two-tailed P = Idf/(df+t²)(df/2, 1/2).
F (Fisher–Snedecor): P = Idfd/(dfd+dfn·F)(dfd/2, dfn/2) via the same incomplete beta implementation.
r (Pearson correlation): Converted to a t statistic: t = r√(df) / √(1 − r²), then evaluated against Student's t with the given df.
Chi-square: P = 1 − γ(df/2, χ²/2) / Γ(df/2), using the regularized incomplete gamma function computed via series expansion (small x) or Legendre's continued fraction (large x).