Question 1. (10 points)

We are using data on 2,181 respondents aged 18 and older from the 2016 General Social Survey to estimate a linear regression model that estimates the association between work hours and education (r=0.172). The data table below provides you with some basic information about the two variables that we are using to estimate this association and explore this focal relationship.

	Mean (SD)	Minimum	Maximum
Education (years of schooling)	13.80 (2.90)	0	20
Work Hours (hours per week)	29.07 (22.46)	0	89

1. Using the information provided in the table and in the question prompt, calculate the slope coefficient for a linear regression that estimates work hours as a function of one's education.
2. One respondent's information is a point directly on the regression line we are estimating. They have completed 14 years of schooling and work 31 hours per week. Use this information and the coefficient calculated in (a) to calculate the intercept coefficient of this linear regression.
3. Interpret the estimated slope coefficient. What does it mean substantively?
4. Interpret the estimated intercept coefficient. What does it mean substantively?
5. Use the linear regression model that we've calculated to extrapolate outside the sample. What would be a person's predicted weekly hours if they completed 21 years of education, according to this model? Make sure to write out the complete linear regression model as part of your work.