Cost Estimation; High-Low and Regression Methods 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 openings—the 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:
Required
1. Using the high-low cost estimation technique and square feet as the independent variable, determine the cost of painting a 3,300-square-foot house with 14 external openings. Also determine the cost for a 2,400-square-foot house with 8 externals openings.
2. Repeat requirement 1, but use number of external openings as the independent variable.
3. Plot the cost data against square feet and against openings. Which variable is a better cost driver? Why?
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.
5. What are the sustainability issues for this company, and what is the role of cost estimation in this regard?