Overview
Chapter 10 in the textbook; Tanner, D. (2016). Statistics for the behavioral & social sciences (2nd ed.). Bridgepoint Education. https://content.uagc.edupages; 109 to 120 in Chapter 7 of the Jarman (2013) e-book;Jarman, K. H. (2013). https://ebookcentral.proquest.com/lib/ashford-ebooks/detail.action?docID=1175199: the Chi-Square Test (Links to an external site.), The Chi-Square Test: Often Used and More Often Misinterpreted (Links to an external site.), The Chi-Square Test of Independence (Links to an external site.), How to Chi-Square Test (Links to an external site.), and How to Interpret Chi-Squared (Links to an external site.) articles; watch the Two-Way Tables: Against All Odds - Inside Statistics (Links to an external site.), Chi-Square Tests: Crash Course Statistics #29 (Links to an external site.), Chi-Square Test for Association (Independence) | AP Statistics | Khan Academy (Links to an external site.), and Chi-Square: Lecture 11
The purpose of this discussion is to allow you to consider how nonparametric tests are used and how two types of chi-square tests compare. To do this, you will need to explain statistical concepts and assess assumptions, limitations, and implications associated with statistical tests.
For your initial post,
Describe the chi-square goodness-of-fit test. Explain what this test measures.
Explain how the chi-square goodness-of-fit test is similar to and different from a simple frequency distribution.
Describe the chi-square test of independence. Explain what this test measures and how it is similar to and different from the chi-square goodness-of-fit test.
How do you know when to use one analysis over the other?
Provide a real-world example in which either a goodness-of-fit test or a test of independence should be used.