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Fisher's Exact Test (2×2 Table)
x402
Fisher's Exact Test (2×2 Table) is a paid API for AI agents from stats-tests.x402tookit.com, paid per call via x402, $0.02/call, status unknown (last checked 2026-10-21).
Computes two-sided and one-sided p-values via the hypergeometric distribution and the sample odds ratio for a 2×2 contingency table using Fisher's exact test.
Price / call$0.02
Success—
StatusUnknown
How this service works
Fisher's exact test for a 2x2 table: two-sided and one-sided p-values from the hypergeometric distribution, plus odds ratio.
Output
Returns the two-sided p-value, one-sided p-values (less and greater), the sample odds ratio, the probability of the observed table under the null hypothesis, and a flag indicating whether the result is significant at the 5% level.
Example use cases
Clinical trial response rate comparison
“I ran a small drug trial — 8 patients responded and 4 didn't in the treatment arm, and 2 responded and 10 didn't in the placebo arm. Can you run Fisher's exact test and tell me if the difference is statistically significant, with the two-sided p-value and odds ratio?”
A/B test conversion significance check
“In my A/B test, variant A had 45 conversions out of 55 shown, and variant B had 30 conversions out of 50 shown. Run Fisher's exact test on those four counts and tell me the p-values and odds ratio.”
Genetic association study
“For my genetics data, 18 cases had the risk allele and 7 didn't, while 5 controls had the risk allele and 20 didn't. What does Fisher's exact test say — is the association significant, and what's the odds ratio?”
Technical details
Endpoint
GEThttps://stats-tests.x402tookit.com/fisher-exact?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a 2×2 contingency table with small expected cell counts (where chi-square approximations are unreliable), or when you need exact p-values from the hypergeometric distribution rather than asymptotic approximations. It is ideal for clinical trials, genetic association studies, and any binary exposure/outcome setup with limited sample sizes.
Side effects
- Missing any of the four required integer counts (a, b, c, d) results in a validation error
- Non-integer or negative cell counts will be rejected
- All-zero marginals (e.g., an entire row or column is zero) may produce undefined odds ratio
- Very large counts may produce floating-point precision edge cases
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
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