Chi Square Test for Independence

Chi Square Test for Independence
Description	Chi Square Test for Independence determines whether two categorical variables are related or independent.
Why to use	To test the independence or association between categorical variables.
When to use	When the dataset contains at least two categorical variables.	When not to use		On Continuous data
Prerequisites	The data should be categorical.
Input	Two categorical variables	Output	Chi Square Statistic Observed Frequency Table and Expected Frequency Table for the selected categorical Variables
Statistical Methods used	—	Limitations	It can be used only on categorical data.

The Chi Square Test for Independence is a hypothesis test. It compares two categorical variables to check if they are related to each other or not. It uses a contingency table (cross table) for the analysis of data. In a cross table, the data is classified according to the two categorical variables. The categories for one variable appear in the rows, while the categories for another variable appear in columns. Each cell represents the total count of cases for a specific pair of categories.