Fisher's Exact Test Calculator
Quickly calculate Fisher's Exact Test for 2x2 contingency tables to assess the association between two categorical variables. Ideal for small sample sizes.
Enter Contingency Table Data
Input the values for your 2x2 contingency table. These values represent the counts for each category in your study.
Set Significance Level (α)
Enter the significance level (alpha). Typically, α is set to 0.05. This is the probability of rejecting the null hypothesis when it is true.
Result: Fisher's Exact Test
The p-value is the probability of observing a contingency table as extreme as, or more extreme than, the observed table, assuming there is no association between the variables.
For a significance level (α) of , we the null hypothesis.
Understanding the Result
Fisher's exact test evaluates whether there is a statistically significant association between two categorical variables.
| Category 1 Outcome | Category 2 Outcome | |
|---|---|---|
| Group 1 | ||
| Group 2 |
The calculated p-value helps determine if the observed association is likely due to chance or if it reflects a real relationship between the categories.
Understanding Fisher's Exact Test
Fisher's Exact Test is a statistical test used to determine if there is a significant association between two categorical variables. It is particularly useful when dealing with small sample sizes, where approximations from other tests like the Chi-squared test may not be accurate.
Contingency Table: The test is based on a 2x2 contingency table, which summarizes the counts of observations for two categorical variables. The rows and columns represent the categories of the two variables.
P-value: The p-value calculated by Fisher's Exact Test represents the probability of observing the current contingency table, or one more extreme, if there were truly no association between the variables (null hypothesis). A small p-value (typically ≤ 0.05) suggests that there is evidence to reject the null hypothesis and conclude that there is a statistically significant association.
When to Use: Use Fisher's Exact Test when you have categorical data in a 2x2 table, especially when sample sizes are small, or when expected cell counts are low. It's a robust test for association in such scenarios.
For more detailed information, you can refer to resources on statistical hypothesis testing and categorical data analysis.