P-value Calculator

How it works

Matching a p-value to the test direction

Select the test direction and distribution assumptions that match the question being tested. One-sided and two-sided probabilities can differ for the same standardized statistic. A p-value describes evidence under the specified null model; it is not the probability that a hypothesis is true or a measure of practical importance. Interpret it alongside the effect size and study design.

P-value: formula and assumptions

A tail probability measures how extreme the statistic is under the stated null distribution.

Select the test distribution and relevant degrees of freedom. A p-value is not the probability that the null hypothesis is true.

Normal probabilities & inverse: formula and assumptions

Left=Φ(z); right=SF(z); central=1−2SF(|z|); outside=2SF(|z|).

Probabilities use the interval 0–1, not percentages. A central probability determines the magnitude of z; both signs are shown.

Worked example

Using the P-value example:

Distribution

Standard normal (z)

Test statistic

1.96

A tail probability measures how extreme the statistic is under the stated null distribution.

Example result

• Interpret the tail that matches your prespecified hypothesis.

These are illustrative inputs. Change the values to explore a different scenario.

Formula references

• OpenStax: Algebra and Trigonometry (opens in a new tab)
• NIST statistical methods handbook (opens in a new tab)

References explain the underlying methods; they do not imply endorsement or individual professional review of Finflo.

Common questions