Multiple Regression Output for Internet Hours per Week, Educational Attainment, and Age Model Summary Adjusted R Std. Error of Model R R Square Square the Estimate 319 101 099 16.402 a. Predictors: (Constant), Age of respondent, Highest year of school completed ANOVA Sum of Model Squares df Mean Square Sig. Regression 19173.948 9586.974 35.637 .000 Residual 169748.495 631 269.015 Total 188922.443 633 a. Dependent Variable: Www hours per week b. Predictors: (Constant), Age of respondent, Highest year of school completed Coefficientsa Standardized Unstandardized Coefficients Coefficients Model B Std. Error Beta Sig. (Constant) 21.827 3.746 5.827 000 Highest year of school .515 .237 082 2.171 030 completed Age of respondent -.309 .037 -.311 -8.235 000 a. Dependent Variable: Www hours per week 1. Interpret the R-square value for this model. 2. Interpret the coefficients for Highest Year of School Completed and Age. 3. Interpret the constant. 4. Are these results significant? How would you interpret the overall model taking into account the coefficients, significance, and R-square values? 5. Do these results make sense to you? Why or why not