Data Analysis Procedure: Fisher's Exact Test Research Design

Data Analysis Procedure: Fisher’s Exact Test
Research Design: Causal Comparative
Type of Data: Nominal
Number of Groups: 2
Sample Type: Paired samples
Description of Test:
Fisher's exact test is a statistical significance test used for small sample sizes. It is one of a number of tests
used to analyze contingency tables, which display the interaction of two or more variables. This test was
invented by English scientist Ronald Fisher, and it is called exact because it calculates statistical significance
exactly, rather than by using an approximation.
To understand how Fisher's exact test works, it is essential to understand what a contingency table is and how
it is used. In the simplest example, there are only two variables to be compared in a contingency table. Usually,
these are categorical variables. As an example, imagine you are conducting a study on whether gender
correlates with owning pets. There are two categorical variables in this study: gender, either male or female,
and pet ownership. Source:
The Fisher exact test for 2 x 2 tables is used when members of two independent groups can fall into
one of two mutually exclusive categories. The test is used to determine whether the proportions of
those falling into each category differ by group. The chi-square test of independence can also be used
in such situations, but it is only an approximation, whereas Fisher's exact test returns exact one-tailed
and two-tailed p-values for a given frequency table. Source:
Video URL:
Resource URL: