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Free Fisher's exact test calculator. Calculate p-values, odds ratios, and confidence intervals for 2x2 contingency tables with step-by-step solutions. Our calculator uses statistical principles to determine all test relationships from any given contingency table.
Last updated: February 2, 2026
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0.0500
Statistical significance
3.000
Association strength
2.440
Test statistic
1
Degrees of freedom
[0.900, 9.000]
Given contingency table:
10 5
8 12
Calculate expected values:
7.71 7.29
10.29 9.71
Calculate odds ratio: (10 × 12) / (5 × 8) = 3.000
Calculate p-value: 0.0500
Result: Not significant at α = 0.05
Exact Test
Fisher's exact test for 2x2 contingency tables
Odds Ratio
Odds ratio calculation with confidence interval
Confidence Interval
Confidence interval for odds ratio
Method used
Exact Test
Exact p-value calculation
Formula used
OR = (a×d)/(b×c)
Association strength measure
Formula used
χ² = Σ(O-E)²/E
Independence test
Method used
95% CI
Statistical inference
Features
Complete Analysis
Comprehensive statistical calculations
Applications
Clinical Trials
Medical research applications
For contingency table [10, 5; 8, 12]:
P-Value
0.0500
Odds Ratio
3.000
Chi-Square
2.400
DF
1
Our Fisher's exact test calculator uses the fundamental principles of statistical analysis to calculate exact p-values, odds ratios, and confidence intervals for 2x2 contingency tables. The calculation applies statistical methods and hypothesis testing to determine all test relationships.
Odds Ratio = (a × d) / (b × c)Chi-Square = Σ(O - E)² / EExpected Value = (Row Total × Column Total) / Grand TotalP-Value = P(observed or more extreme | H₀)These formulas form the foundation of statistical hypothesis testing and allow determination of all test relationships from any given contingency table. They apply to both small and large sample sizes.
Shows the statistical test process from contingency table to p-value
Fisher's exact test is a fundamental statistical method used to test the independence of two categorical variables in a 2x2 contingency table. It's based on the hypergeometric distribution and provides exact p-values, making it particularly useful for small samples where the chi-square test assumptions are violated.
Need help with other statistical calculations? Check out our chi-square calculator and t-test calculator.
Get Custom Calculator for Your PlatformResult: p = 0.0500, OR = 3.000, 95% CI: [0.500, 18.000]
The test shows no significant association between the variables at α = 0.05.
Treatment vs. Control
Result: p = 0.02, Significant
Disease vs. Exposure
Result: p = 0.25, Not significant
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