Description

Overview:
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 variablesOrganize data into two-way tablesStudy joint, marginal and conditional distributions and learn the relationship between themObserved and expected frequencies, Chi-Square test statisticChi-Square test of independence – set up hypothesis, use technology to run the test and interpret P-valueTextbook Material -  ·         Chapter 11.3 – Test of Independence – Pages 627 - 632
Subject:
Statistics and Probability
Level:
Community College / Lower Division, College / Upper Division
Material Type:
Module
Provider:
Ohio Open Ed Collaborative
Date Added:
07/03/2018
License:
Creative Commons Attribution-NonCommercial 4.0 Creative Commons Attribution-NonCommercial 4.0
Language:
English
Media Format:
Text/HTML

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