Please answer requirements 3b and 4.
Required information [The following information applies to the questions displayed below.] The Mac Davis Company specializes in the purchase, renovation, and resale of older homes. Mac employs several carpenters and painters to do the work for him. It is essential for him to have accurate cost estimates so he can determine total renovation costs before he purchases a piece of property. If estimated renovation costs plus the purchase price of a house are higher than the house's estimated resale value, it is not a worthwhile investment. Mac has been using the home's interior square feet for his exterior paint cost estimations. Recently he decided to include the number of external openingsthe total number of doors and windows in a house-as a cost driver. Their cost is significant because they require time-consuming preparatory work and careful brushwork. The rest of the house usually is painted either by rollers or spray guns, which are relatively efficient ways to apply paint to a large area. Mac has kept careful records of these exterior painting costs on his last 12 jobs: House 1 2 3 4 5 6 7 8 9 10 11 12 Square Feet 2,500 3,010 2,800 2,850 4,600 2,700 2,600 2,550 2,600 3,700 2,660 3,550 External Openings 13 15 12 12 19 13 11 11 10 16 13 16 Costs $ 2,810 3,742 3,100 3,150 4,700 3,225 2,920 2,836 3,242 4,112 3,220 3,965 Required: 3b. From reviewing the graph you created, which of the variables is a good cost driver? 4. Create a multiple regression model for predicting cost based on openings and square feet. Comment on the statistical reliability and precision of this model. Complete this question by entering your answers in the tabs below. Reg 3B Reg 4 From reviewing the graph you created, which of the variables is a good cost driver? Good cost driver square feet openings both Req 3B Req 4 Create a multiple regression model for predicting cost based on openings and square feet. Comment on the statistical reliability and precision of this model. (Choose values closest to your computations from the dropdowns below.) Overall, the regression is with an R-squared of at which is a relatia mall narantone and standard error of the estimate (SE), of the mean of the dependent variable, (1%) (5%) (16%) Req 3B Req 4 Create a multiple regression model for predicting cost based on openings and square feet. Comment on the statistical reliability and precision of this model. (Choose values closest to your computations from the dropdowns below.) Overall, the regression is with an R-squared of at which is a relatively small percentage and standard error of the estimate (SE), of the mean of the dependent variable,
