An association between two variables explains how one variable changes in response to changes in the other variable. A lack of association indicates that the two variables are independent of each other, meaning the chances of events of one variable are not affected by the occurrence or non-occurrence of events of the other variable. In this module we will learn about the different tools used for analyzing associations in two-variable categorical data sets.

Learning Objectives:

• Identify response and explanatory variables
• Organize data into two-way tables
• Study joint, marginal and conditional distributions and learn the relationship between them
• Observed and expected frequencies, Chi-Square test statistic
• Chi-Square test of independence – set up hypothesis, use technology to run the test and interpret P-value

Textbook Material - 

·         Chapter 11.3 – Test of Independence – Pages 627 - 632