Suppose the Sherwin-Williams Company has developed the following multiple regression model, with paint sales Y (x...
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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=a+BaA+BpP+EY=a+BaA+BpP+ε Now suppose that the estimate of the model produces following results: a=344.585a=344.585, ba=0.102ba=0.102, bp=-13.397bp=-13.397, sba=0.155sba=0.155, sbp=4.312sbp=4.312, R2=0.813R2=0.813, Note that the sample consists of 10 observations. and F-statistic-11.361F-statistic-11.361. According to the estimated model, holding all else constant, a $1,000 increase in promotional expendituresincreases sales by approximately 102 gallons. Similarly, a $1 increase in the selling pricedecreases sales by approximately 13,397 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? 0.155 0.813 0.102 The given F-value shows that youcan 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 $12.50? 187.322 212.772 166.922 When promotional expenditures are $80,000 and the selling price is $12.50, the point price elasticity is, and the point promotional price elasticity is. 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=a+BaA+BpP+EY=a+BaA+BpP+ε Now suppose that the estimate of the model produces following results: a=344.585a=344.585, ba=0.102ba=0.102, bp=-13.397bp=-13.397, sba=0.155sba=0.155, sbp=4.312sbp=4.312, R2=0.813R2=0.813, Note that the sample consists of 10 observations. and F-statistic-11.361F-statistic-11.361. According to the estimated model, holding all else constant, a $1,000 increase in promotional expendituresincreases sales by approximately 102 gallons. Similarly, a $1 increase in the selling pricedecreases sales by approximately 13,397 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? 0.155 0.813 0.102 The given F-value shows that youcan 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 $12.50? 187.322 212.772 166.922 When promotional expenditures are $80,000 and the selling price is $12.50, the point price elasticity is, and the point promotional price elasticity is.
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Managerial economics applications strategy and tactics
ISBN: 978-1439079232
12th Edition
Authors: James r. mcguigan, R. Charles Moyer, frederick h. deb harris
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