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How to interpret spss outputs for measures of association

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Reference no: EM131673116

Textbooks

1. OpenStax, Introductory Statistics. OpenStax. 19 September 2013.

2. Tyrrell, S. 2009. SPSS: Stats practically short and simple (1st edition).

Original Question:

In week 3, we used epsilons and 10-percent-point rule to determine if a potential relationship between two variables is worth examining further.

This week, we'll use tests of "measures of association" to figure out the exact strength of a relationship between two variables. In addition, we'll learn how to interpret SPSS outputs for measures of association tests such as lambda, gamma, and Pearson's r, along with other possible tests.

Remember that these tests are specific to the level of measurement that your variables are. In other words, one test may not work in a different relationship test. Here are the guidelines:

1. Both DV and IV are nominal variables: Lambda (when it is not a 2X2 table)

a. If it is a 2X2 table: Phi

2. Both DV and IV are ordinal variables: Gamma

3. One variable ordinal AND the other variable dichotomous nominal (like Yes/No, male/female, etc.): Gamma

a. One variable ordinal AND the other variable nominal (not dichotomous, has more than 2 categories): Cramer's V.

4. Both DV and IV are I/R variables: Pearson's r

Attachment:- measures of association.rar

Reference no: EM131673116

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