SOC Load the GSS2012 data set and analyze the relationships between number of hours spent on the

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SOC Load the GSS2012 data set and analyze the relationships between number of hours spent on the Internet each week (the dependent or Y variable), and two independent variables: age and years of education. We will use both partial correlation and multiple regression and correlation to examine these relationships.

● Partial Correlation Analysis: Is the relationship between wwwhr and age affected by educ?

● Get the zero-order correlations first:

● Click Analyze S Correlate S Bivariate.

● Enter wwwhr, educ, and age in the Variables: window.

● Click Analyze S Correlate S Partial

● Enter wwwhr and age in the “Variables:” window and educ in the “Controlling for:” window.

● Click OK.

● Multiple Regression and Correlation: What are the effects of educ and age on wwwhr?

● Click Analyze S Regression S Linear.

● Move wwwhr to the “Dependent” window and age and educ to the “Independent” window

● Click Statistics and check “Descriptives.” Click Continue to return to the “Linear Regression”

screen.

● Click OK.

a. Summarize the results for the partial correlation analysis in a paragraph in which you report the value of the zero-order and partial correlation.

Does the relationship between wwwhr and age seem to be direct?

b. State the unstandardized multiple regression equation. (HINT: The values for a and b are in the “Coefficients” box of the output, under the column labeled B. The value in the first row is a and the values in the second and third rows are the slopes or b.)

Y 5 ___ 1 ___ X1 1 ___ X2

c. State the standardized multiple regression equation. What is the direction of each relationship?

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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Which independent variable had the stronger effect on wwwhr? (HINT: The beta-weights are in the “Coefficients” box, under “Standardized Coefficients” and “Beta”).
Zy 5 ____ Z1 1 ___ Z2

d. Report the value of R2 . What percentage of the variance in wwwhr is explained by the two independent variables combined? How does this compare to the amount of the variance explained by each independent variable alone? (HINTS: R2 is in the “Model Summary” box and you can compute r 2 from the r’s in the “Correlations” window of the output.)
Bivariate: r r 2 wwwhr and educ age Multiple: R 2 5

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