Fisher’s Exact Test: Definition, Formula, and Example


Fisher’s Exact Test is used to determine whether or not there is a significant association between two categorical variables. It is typically used as an alternative to the Chi-Square Test of Independence when one or more of the cell counts in a 2×2 table is less than 5. 

Fisher’s Exact Test uses the following null and alternative hypotheses:

  • H0: (null hypothesis) The two variables are independent.
  • H1: (alternative hypothesis) The two variables are not independent.

Suppose we have the following 2×2 table:

Group 1 Group 2 Row Total
Category 1 a b a+b
Category 2 c d c+d
Column Total a+c b+d a+b+c+d = n

The one-tailed p value for Fisher’s Exact Test is calculated as:

p = (a+b)!(c+d)!(a+c)!(b+d)! / (a!b!c!d!n!)

This produces the same p value as the CDF of the hypergeometric distribution with the following parameters:

  • population size = n
  • population “successes” = a+b
  • sample size = a + c
  • sample “successes” = a

The two-tailed p value for Fisher’s Exact Test is less straightforward to calculate and can’t be found by simply multiplying the one-tailed p value by two. To find the two-tailed p value, we recommend using the Fisher’s Exact Test Calculator.

Fisher’s Exact Test: Example

Suppose we want to know whether or not gender is associated with political party preference. We take a simple random sample of 25 voters and survey them on their political party preference. The following table shows the results of the survey:

Democrat Republican Total
Male 4 9 13
Female 8 4 12
Total 12 13 25

Step 1: Define the hypotheses.

We will perform Fisher’s Exact Test using the following hypotheses:

  • H0Gender and political party preference are independent.
  • H1: Gender and political party preference are not independent.

Step 2: Calculated the two-tailed p value.

We can use the Fisher’s Exact Test Calculator with the following input:

Fisher's Exact test example

The two-tailed p value is 0.115239. Since this value is less than 0.05, we fail to reject the null hypothesis. We do not have sufficient evidence to say that there is any statistically significant association between gender and political party preference.

Additional Resources

The following tutorials explain how to perform a Fisher’s Exact Test using different statistical programs:

How to Perform Fisher’s Exact Test in R
How to Perform Fisher’s Exact Test in Excel
How to Perform Fisher’s Exact Test in Stata
How to Perform Fisher’s Exact Test in SPSS
How to Perform Fisher’s Exact Test in Python
Fisher’s Exact Test Calculator

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9 Replies to “Fisher’s Exact Test: Definition, Formula, and Example”

  1. Hi Zach, can you double check your conclusion regarding the p-value in your example? You wrote: “The two-tailed p value is 0.115239. Since this value is less than 0.05, we fail to reject the null hypothesis. “. But…. your calculated p value is GREATER THAN 0.05, so should we be rejecting the null hypothesis?

  2. “Since this value is less than 0.05, we fail to reject the null hypothesis. ” This looks like in needs some fixing.

  3. The two-tailed p value is 0.115239. Since this value is less than 0.05 ?

    I would say that 0.115239 > 0.05…

  4. The two-sided p value is 0.115239, which is greater than 0.05. Not “less than 0.05”, maybe just typo.

  5. Hi, I think you may need a correction on the sentence “The two-tailed p value is 0.115239. Since this value is less than 0.05, we fail to reject the null hypothesis” which should say “The two-tailed p value is 0.115239. Since this value is *not* less than 0.05, we fail to reject the null hypothesis”…
    Thanks for the great site!

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