P-value Calculator
Adjust the inputs below. Results update as you type.
How it works
The p-value is the probability of observing a result as extreme as the test statistic if the null hypothesis is true. p < 0.05 is the conventional threshold for statistical significance—but this is arbitrary and context-dependent. p-value does not measure effect size or practical importance. A very small p with a tiny effect size may be unimportant. Always report confidence intervals alongside p-values.
Input guidance
- Check units and decimal placement before running calculations.
- For percentage and ratio tasks, define the baseline value clearly.
- Use rounded output carefully and keep full precision for intermediate steps.
The formula
A p-value is the probability of observing results at least as extreme as your data if the null hypothesis were true, computed from a test statistic and its distribution.
Worked example
A p-value of 0.03 against a 0.05 threshold means the result is statistically significant — there is a 3% chance of seeing it by chance alone if the null were true.
More examples to test
- Baseline example: solve with clean numbers first to verify formula direction.
- Edge-case example: test near-zero or boundary values to avoid interpretation errors.
How to interpret results
Use outputs as quick checks, then verify with step-by-step work for graded or high-stakes use.
When this can be inaccurate
Errors usually come from unit mismatch, wrong baseline assumptions, or rounding too early in multistep problems.
Change history
- July 2026: Quality-reviewed for publication with formula checks and explanatory copy updates.
Site-wide corrections also appear on the corrections log.
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Educational platform recommendation.
Frequently asked questions
What does a p-value mean?+
The chance of getting your observed result (or more extreme) if there were truly no effect. Small p-values cast doubt on the null hypothesis.
What is statistical significance?+
A result is often called significant if the p-value is below a chosen threshold (commonly 0.05), suggesting the effect is unlikely to be pure chance.
Does a small p-value prove my hypothesis?+
No. It only suggests the data is unlikely under the null. It does not measure effect size or prove causation, and thresholds are conventions, not proof.
Why do my classroom and calculator results differ?+
Differences usually come from rounding conventions, order-of-operations handling, or different baseline assumptions.
What is the safest way to validate an answer?+
Recompute with units shown and check against a second method or manual arithmetic for critical problems.