The following regression predicts hours of TV watched per day based on number of hours worked a day, age, and marital status. Coefcient Intercept 2.00 Hours Worked 0.08 Age 0.03 Marital Status (1=married, 0=unmarried) 0.01 Using this table, how much TV would we expect a married 40 yearold who worked 7 hour days to watch? : QUESTION 21 The following regression predicts life expectancy as a function of an individual's number of drinks a week. hours spent exercising a week, and sex. Coefcient Intercept 75.92 Number of Drinks a Week 0.1 3 Hours of Exercise 0.03 Male (1=male, 0=female) 2.55 Using this table. what would we expect the life expectancy to be for man who drinks 10 drinks a week and doesn't exercise. : The following regression predicts hours studied in college students as a function of years in school, number of friends, and majoring in a STEM field. Coefficient p-value Intercept 8.83 0.12 Years in School 0.15 0.04 Number of Friends 0.01 0.01 Majoring in STEM field (1=yes, 0=no) | 3.81 0.13 Using this table, how much would we expect a student to study who is in their 2nd year, has 10 friends, and is majoring in a STEM field