Question.4104 - ?Assignment Six: Using Pearsons r and r2 to analyze and interpret associations between two interval/ratio variables Part I: Use APA style and formatting for all assignments, references, and citations. Yes, have a cover page, too, as well as a running head. Try Purdue Owl for an example APA style paper: https://owl.english.purdue.edu/owl/resource/560/18/ Follow the directions in your text for demonstration 14.2, and 14.3 in the 11th edition, using SPSS to compute Pearsons r and requesting several correlation coeeficients. You will be using pincp, agep, and schl for this analysis. Make sure to turn on your weight variable. The weight variable is pwgtp. Which variables are your dependent and independent variables? Hint: you should have two independent variables. Dependent: Independent: Independent: You will notice that you do not have to do any recoding because we are using the pincp, age, and schl variables that are interval/ratio variables already in the ACS dataset (schl is technically ordinal but we are treating it as an interval ration measure). For r and r2, you must use interval/ratio variables for the dependent variable. This is one of the reasons why I chose for us to use the ACS dataset. It, unlike the GSS dataset, has income as an interval/ratio and continuous measure. You can use nominal and ordinal measures for the independent variables even though we are not doing that right now. 14.2 will help you compute the association, Pearsons r, for age and pincp. Copy and paste your output that looks like correlations in your text on page 252 in the 11th edition. You can also check the example assignment in the module to see what the output should look like. What is the Pearsons r for the association between age and pincp? What is r2 for this association? Remember minimal calculations, but you need to square Pearsons r for this answer. What is the strength of the association according to your text on page 249? What is the direction of the association? What does this mean? Using the PRE logic, how much of the variation in pincp can be attributed to age in your sample? 14.3 asks you to look at correlations among three variables, one dependent and two independent. So, for this analysis you will add schl to your correlation analysis. Copy and paste your output that looks like correlations on page 257 of your text. What is the Pearsons r for the association between pincp and schl? What is r2 for this association? What is the strength of the association? What is the direction of the association? What does this mean? Using the PRE logic, how much of the variation in pincp can be attributed to schl in your sample? Finally, which independent variable explains more of the variation in income, age or education? Now, and this is very important. Make some concluding statements about the effect of education and age on income for the full-time year-round workers in our sample. You need to write full sentences using the analysis results to support your conclusions. Take a look at the writing boxes in your chapter to help.
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