Question

Exercise 4.8 Suppose the Sherwin-Williams Company has developed the following multiple regression model, with paint sales Y (x 1,000 gallons) as the dependent variable and promotional expenditures A (x $1,000) and selling price P (dollars per gallon) as the independent variables. Y=α+βaA+βpP+εY=α+βaA+βpP+ε Now suppose that the estimate of the model produces following results: α=344.585α=344.585 , ba=0.106ba=0.106 , bp=−12.112bp=−12.112 , sba=0.155sba=0.155 , sbp=4.421sbp=4.421 , R2=0.813R2=0.813 , and F-statistic=10.372F-statistic=10.372 . Note that the sample consists of 10 observations. According to the estimated model, holding all else constant, a $1,000 increase in promotional expenditures selector 1    decreases increases sales by approximately selector 2    106 12,112 813 gallons. Similarly, a $1 increase in the selling price selector 3    increases decreases sales by approximately selector 4    106 813 12,112 gallons. Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining paint sales? Check all that apply. Selling price (P) Promotional expenditures (A) What proportion of the total variation in sales is explained by the regression equation? 0.813 0.106 0.155 The given F-value shows that you selector 1    can cannot reject the null hypothesis that neither one of the independent variables explain a significant (at the 0.05 level) proportion of the variation in income. Based on the regression model, what is the best estimate of paint sales (x 1,000 gallons) in a sales region where promotional expenditures are $100,000and the selling price is $11.50? 235.907 194.697 215.897 When promotional expenditures are $80,000 and the selling price is $11.50, the point price elasticity is selector 1    -0.590 -0.715 -0.645 , and the point promotional price elasticity is selector 2    0.054 0.049 0.045 .

Answer 1