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Unit 8

8.4 Expected Counts in Two Way Tables

2 min readapril 28, 2021

josh

Josh Argo


8.4: Expected Counts in Two Way Tables

Tests from Two-Way Tables

Another form of data that we can use χ2 tests for involves data from a two-way table (like the one pictured below).
https://firebasestorage.googleapis.com/v0/b/fiveable-92889.appspot.com/o/images%2F-SIlivsw3yjOF.png?alt=media&token=896232ae-57d0-4295-afdd-e16338450354

Image Taken from MathBitsNotebook

When performing a χ2 test from a two way table, there are two different tests we may have to perform and choosing which one can be tricky.
Test for Homogeneity
When we are comparing two different populations and if two different populations have different amounts for a given categorical variable, we would use a χ2 test for homogeneity.
Test for Independence
When we are comparing within ONE population to see if two categorical variables are associated within the one population, we would use a χ2 test for independence.

Expected Counts

Regardless of which test we are doing, we will be comparing two multi-row/column matrices rather than just two rows or columns. This means we have to calculate the expected counts matrix based off of our observed counts table. This will be done by doing the following for each cell: 
(observed row total)(observed column total)/table total
Example
In the first cell on the two way table above on SUV and sports car ownership in regard to male or female, we would take the total male (60) and the total SUV (156), multiply those to get 9360. Then we would divide that total by our table total (240) and get 39. We would complete this process for all steps to create our expected count table.
Our final expected counts answer would be:
SUV
Sports Car
Male
39
21
Female
117
63

Application

In the next sections, we will talk about setting up the two types of χ2 tests regarding a two way table and how we will use these observed and expected counts to determine if we have association or homogeneity between our two variables/populations.
🎥  Watch: AP Stats Unit 8 - Chi Squared Tests

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