C13. We expand on the model for TVHOURS presented in Exercise 10, adding work hours (HRS1) and respondent age (AGE) as independent variables. Data are based on the GSS 2018.

1. Write the multiple regression equation for the model. Interpret the slope for each independent variable.
2. Based on their beta scores, rank the independent variables according to the strength of their effect on TVHOURS (from the highest to the lowest).
3. Interpret the multiple coefficient of determination.

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Model Model Summary R 155 R Square .024 Adjusted R Square Std. Error of the Estimate .015 1 2.298 a. Predictors: (Constant), Number of hours worked last week, Number of children, Highest year of school completed, Age of respondent Model 1 ANOVA Sum of Squares df Regression Residual 54.032 4 Mean Square 13.508 F Sig. 2.558 .038b Total 2191.251 2245.283 415 419 5.280 a. Dependent Variable: Hours per day watching TV b. Predictors: (Constant). Number of hours worked last week, Number of children, Highest year of school completed, Age of respondent Model 1 (Constant) Highest year of school completed Number of children Age of respondent Number of hours worked last week Coefficients B Unstandardized Coefficients Std. Error Standardized Coefficients Beta t Sig. 3.888 -.083 .715 .039 5.438 .000 -.107 -2.122 .034 -.143 .009 -.014 .086 -.091 -1.657 .098 .009 .058 1.072 .284 .007 -.096 -1.957 .051 a. Dependent Variable: Hours per day watching TV