How to calculate Fisher's Exact Test step-by-step manually.

📚 Quick Study Guide

• 🔢 Fisher's Exact Test is used for categorical data when sample sizes are small, and the assumptions of the Chi-squared test are not met.
• 📝 It determines if there's a significant association between two categorical variables.
• 📊 The data is typically organized in a 2x2 contingency table.

  	Category 1	Category 2
  Group 1	a	b
  Group 2	c	d

• 🧮 The formula to calculate the p-value for Fisher's Exact Test is: $ p = \frac{(a+b)!(c+d)!(a+c)!(b+d)!}{N!a!b!c!d!} $ where N = a + b + c + d.
• 💡 The p-value is the sum of probabilities of observing the actual table and more extreme tables.
• 🔍 A small p-value (typically ≤ 0.05) suggests a significant association.

Practice Quiz

1. What type of data is Fisher's Exact Test used for?
   1. Numerical data
   2. Categorical data
   3. Continuous data
   4. Ordinal data
2. When is Fisher's Exact Test most appropriate?
   1. When sample sizes are large
   2. When sample sizes are equal
   3. When sample sizes are small
   4. When data is normally distributed
3. What does a small p-value (e.g., ≤ 0.05) in Fisher's Exact Test indicate?
   1. No association between the variables
   2. A strong association between the variables
   3. A moderate association between the variables
   4. A data entry error
4. Which test is often used as an alternative to Fisher's Exact Test when sample sizes are large?
   1. T-test
   2. ANOVA
   3. Chi-squared test
   4. Regression analysis
5. In a 2x2 contingency table, what does 'N' represent in the Fisher's Exact Test formula?
   1. The smallest value in the table
   2. The total number of observations
   3. The number of rows
   4. The number of columns
6. What does Fisher's Exact Test determine?
   1. The correlation coefficient between two variables
   2. If there is a statistically significant association between two categorical variables
   3. The mean difference between two groups
   4. The standard deviation of a sample
7. What is the next step after calculating the probability of the observed table?
   1. Stop calculation and accept the results
   2. Calculate probabilities of more extreme tables
   3. Divide the result by 2
   4. Multiply the result by 2