• Check the conditions for Fisher’s Exact Test
• Explain the relationship of two qualitative binary variables using Fisher’s Exact Test

Fisher’s Exact Test

Fisher’s Exact Test (also known as Fisher’s Exact Test of Independence) is a statistical significance test used in the analysis of a [latex]2 \times 2[/latex] contingency table.

It is used to determine whether or not there is a significant association between two categorical variables.

Let’s revisit the motorcycle example.

A 2004 study titled “Motorcycle rider conspicuity and crash related injury: case-control study” looked at a similar context and, based on the conclusions of that study^[1], the researcher decides to combine cells from the table below into a two-way table.

[Trouble viewing? Click to open in a new tab.]

Conditions for using the chi-square test for independence:

• Independence/Randomness Condition: The sample from our population should be independent, random sample or independent sample that can be considered representative of the population.
• Large Sample Sizes Condition: The sample sizes need to be large enough so that the expected count in each cell is at least five.

---