Below I will list some regressions and regression results. Please draw the predicted values for all of the different groups. You do not have to plot them out perfectly. You only have to get the signs, general shape, and relative magnitudes of the coefficients correct. (a) Commute; 10+.02Income; + 15 Suburbi + ei Commute; - The length of person i's commute in minutes Income; - Person i's income Suburbi - 0 if person i lives in the city and 1 if they live in a suburb (b) Sales; = 6000 + 5Advertisingi .0002 Advertising} + 5000 Public; + ei Salesi - The monthly sales for business i Advertisingi - Monthly expenditure on advertising for business i Public; - 0 if company i is privately owned and 1 if it is publicly owned (c) Deer, = 10000 700ln(Permitsi) + ei Deeri - Deer population after hunting season in county i Permitsi - Number of permits granted for hunting season in county i (d) Accidents; = bo + bTraining + b2Incentive; + b3 Incentive x Trainingi + ei Accidentsi - Number of accidents in store i Trainingi - Hours spent training employees on safety protocols in store i Incentive; - 0 if store i does not give monetary incentive to employees for low accidents 1 if they do Below I will list some regressions and regression results. Please draw the predicted values for all of the different groups. You do not have to plot them out perfectly. You only have to get the signs, general shape, and relative magnitudes of the coefficients correct. (a) Commute; 10+.02Income; + 15 Suburbi + ei Commute; - The length of person i's commute in minutes Income; - Person i's income Suburbi - 0 if person i lives in the city and 1 if they live in a suburb (b) Sales; = 6000 + 5Advertisingi .0002 Advertising} + 5000 Public; + ei Salesi - The monthly sales for business i Advertisingi - Monthly expenditure on advertising for business i Public; - 0 if company i is privately owned and 1 if it is publicly owned (c) Deer, = 10000 700ln(Permitsi) + ei Deeri - Deer population after hunting season in county i Permitsi - Number of permits granted for hunting season in county i (d) Accidents; = bo + bTraining + b2Incentive; + b3 Incentive x Trainingi + ei Accidentsi - Number of accidents in store i Trainingi - Hours spent training employees on safety protocols in store i Incentive; - 0 if store i does not give monetary incentive to employees for low accidents 1 if they do
