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we discuss the use of crosstabulations (crosstabs) as a preliminary analysis to
we discuss the use of crosstabulations (crosstabs) as a preliminary analysis to begin investigating the relationship between the IV and DV. A crosstab creates a “snapshot” of our data. Measures of association help to identify the strength and direction of the potential relationship.
You are now going to create and post a crosstab of your variables and a measures of association table.
My Research question: Is there a relationship between an individual’s income and the choice of their presidential candidate?
IV: Is income earned per individual- rincome variable
DV: The presidential candidate- PRES16.
Complete the following steps:
1. Post a brief explanation of your topic. Include your research question and a broad research hypothesis — that is, the relationship of IV to DV. (For example, educational attainment affects family income in US adults.)
2. Run a crosstab on your variables. Be sure to explain your findings, including a description of the table, a calculation of the epsilons, and a discussion of the 10% rule.
3. Run the correct measure of association for your variables (Choose one – either Pearson R, Gamma, Phi, Cramer’s V or Lambda). Explain what the output means in terms of strength and direction of the relationship. Interpret Proportional Reduction of Error (PRE) using the following statement: Knowing the IV will reduce error in predicting the DV by *%.
Copy the crosstab and measure of association table into the discussion window or into a document (PDF, MS Word) and attach to discussion. If your table does not fit to the page, choose “copy special” and then “images” or take a screen shot of the table to copy/past into the window.
Special note:
When a variable is continuous (interval/ratio level of measurement), for example age of respondent, we do not run crosstabs directly because it will result in a really spread-out table with lots of zeros and low frequency cells. Such a crosstab does not help us understand the data. The correct way is to reduce the level of measurement to either ordinal level or nominal level (group the numbers into categories) by recoding and then run the crosstab. (Please refer to the Lesson Recoding in SPSS for further information.)
As a reminder, here are the guidelines for choosing your measure of association:
1. Both DV and IV are nominal variables: Lambda (when it is not a 2X2 table)
2. Both DV and IV are nominal variables and it is a 2X2 table: Phi
3. Both DV and IV are ordinal variables: Gamma
4. One variable ordinal or interval/ratio AND the other variable dichotomous nominal (like Yes/No, male/female, etc.): Gamma
5. One variable ordinal or interval/ratio AND the other variable nominal (not dichotomous, has more than 2 categories): Cramer’s V.
6. Both DV and IV are I/R variables: Pearson’s r
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