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Categorical Data Categorical IV – Categorical DV

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Overview Defined: Frequencies or proportions amongst levels of variables. Variables: IV is categorical, DV is categorical Relationship: Relationship between two or more variables. Example: How do males/females vote guilty or not guilty? Assumptions: Typically you want greater than 5 per cell.

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Final “main” type of analysis

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Theory behind Chi-Square How can you test the relationship between two (or more) categorical variables? Compare the frequency you observe in cells to the frequency you would expect by chance. So compare count (sample) to expected count (population)

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Theory behind Chi-Square How can you test the relationship between two (or more) categorical variables? Compare the frequency you observe in cells to the frequency you would expect by chance. So compare count (sample) to expected count (population)

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Theory behind Chi-Square How can you test the relationship between two (or more) categorical variables?

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Pearson Chi-Square Significance Effect Size Graph

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Pearson Chi-Square If you have more than a 2 x 2… such as 2 x 3, 3 x 2, 3 x 3, etc. … then the output is treated as an “Omnibus” test… …and you conduct the follow-up tests by conducting multiple 2 x 2 tests.

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Example of “Omnibus” and follow-up tests

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