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**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.

When reporting the results of Fisher’s exact test, we usually use the following general structure:

- A brief mention of the two variables.
- The p-value of the test (and whether it represents a one-tailed or two-tailed p-value).

Here’s the exact wording we can use:

Fisher’s exact test was used to determine if there was a significant association between [variable #1] and [#variable 2].

There [was or was not] a statistically significant association between [variable #1] and [variable #2] (p = [p-value]).

The following example shows how to report the results of Fisher’s exact test in practice.

**Example: Reporting Results of Fisher’s Exact Test**

Suppose we want to know whether or not gender is associated with political party preference at a particular college.

To explore this, we randomly survey 25 students on campus. The following table shows the results of the survey:

Democrat | Republican | |
---|---|---|

Female | 8 | 4 |

Male | 4 | 9 |

Since one or more of the cell counts in the table is less than 5, we can use Fisher’s exact test to determine if there is a statistically significant association between gender and political party preference.

Suppose we carry out the test using SPSS and get the following results:

Here is how to report the results of the test:

Fisher’s exact test was used to determine if there was a significant association between gender and political party preference.

There was not a statistically significant association between the two variables (two-tailed p = .115).

**Things to Keep in Mind**

Here are a few things to keep in mind when reporting the results of Fisher’s exact test:

**1. Use a descriptive statistics table.**

It can be helpful to present a descriptive statistics table that shows the total number of individuals used in the survey or study along with the total proportion of individuals that belonged to each variable in order to give the reader a more complete picture of the data.

**2. There is no test statistic to report.**

Unlike a Chi-Square test of independence, Fisher’s exact test has no test statistic to report.

Instead, we simply report the p-value of the test and note that we used Fisher’s exact test. This is a commonly used test, so it’s well known that there will be no test statistic included in the final report.

**Additional Resources**

The following tutorials explain how to perform Fisher’s exact test in various statistical software:

How to Perform Fisher’s Exact Test in R

How to Perform Fisher’s Exact Test in Python

How to Perform Fisher’s Exact Test in SPSS

How to Perform Fisher’s Exact Test in Excel

Fisher’s Exact Test Calculator