2. Estimate a multiple linear regression model where weekly hours spent on the internet is the dependent variable, and age, sex, hours worked, having children, and years of education are the predictor variables. Before estimating the model create a new variable that equals 0 if the person does not have children and equals 1 if the person has any children. a) Write the estimated regression equation. b) Interpret all of the model's slope coefficients. c) Which slope coefficients are statistically significant? How do you know? d) Compare the adjusted R-squared between this model and the model in question 1. Did including additional predictor variables improve explanatory power? e) Use an F-test to test whether the coefficients on hours worked and years of education both equal zero. f) Predict the number of weekly hours spent on the internet for someone who is 30 years old, male, worked 40 hours, has 1 child, and 16 years of formal education. 3. Do you notice any differences in your estimate of the relationship between hours spent on the internet and age between the models in questions 1 and 2