C6. We present SPSS in years) and television viewing per day (measured in hours) based on a GSS 2018 subsample. As we predicted in the SPSS Demonstration, we hypothesize that as educational attainment increases, hours of television viewing will decrease, indicating a negative relationship between the two variables. Discuss the significance of the overall model based on F and its p values. Is the relationship between education and television viewing significant? output examining the relationship between education (measured Linear Regression Output for Hours Spent per Day Watching Television and Education Model Summary Adjusted R Square Std. Error of the Estimate Model R R Square .204 .042 .040 3.176 a. Predictors: (Constant), Highest year of school completed ANOVA Sum of Squares df Mean Square F Sig. Model 1 322.181 31.945 .000 1. Regression 322.181 7402.683 734 10.085 Residual 7724.864 735 Total a. Dependent Variable: Hours per day watching TV b. Predictors: (Constant), Highest year of school completed Coefficients Standardized Coefficients Unstandardized Coefficients Std. Error Beta Sig. Model .000 .527 11.412 6.017 (Constant) .038 -5.652 .000 -.215 -.204 Highest year of school completed a. Dependent Variable: Hours per day watching TV

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Interpret the unstandardized coefficient for highest years of schooling. E.g., Is the relationship positive or negative? How does a one-unit change in schooling (i.e. an increase in one-year of education) influence Y?
- Interpret the constant (i.e. the intercept) in the equation? What does it indicate?
- Calculate the average number of hours watched for someone with 12 years of education.

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