Household Manufacturing has collected the following data on quantity sold (Q), price (P), income (1), and...

 

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Household Manufacturing has collected the following data on quantity sold (Q), price (P), income (1), and advertising (A). Period Quantity, Q Price, P Income, M Advertising, A 1 120 8.0 10 3 2. 165 4.0 22 7 3 120 7.0 20 4 165 3.0 20 8 180 4.0 30 8. 6 90 10.0 19 6 7 150 4.0 18 10.2 8. 190 1.6 25 9.3 9. 160 5.0 30 8. 10 200 2.0 35 9.5 a. Use the multiple regression package such as SPSS or other regression packages to estimate the linear relationship between quantity as the dependent variable and price, income, and advertising as independent variables. Write the linear equation that you find. b. What is the coefficient of determination? Explain what it means? c. Do the signs of the coefficients make economic sense? Which of the coefficients are significant? (alpha = 0.025, df = 6, critical t-statistic = 2.447) d. If Price = 2.0, Income = 35 and Advertising = 9.5, what is the predicted quantity sold? e. Find the price and income elasticities using the information above (d). Interpret the answers. f. Explain how the above model can be used as a forecasting technique. Show how it is done. Household Manufacturing has collected the following data on quantity sold (Q), price (P), income (1), and advertising (A). Period Quantity, Q Price, P Income, M Advertising, A 1 120 8.0 10 3 2. 165 4.0 22 7 3 120 7.0 20 4 165 3.0 20 8 180 4.0 30 8. 6 90 10.0 19 6 7 150 4.0 18 10.2 8. 190 1.6 25 9.3 9. 160 5.0 30 8. 10 200 2.0 35 9.5 a. Use the multiple regression package such as SPSS or other regression packages to estimate the linear relationship between quantity as the dependent variable and price, income, and advertising as independent variables. Write the linear equation that you find. b. What is the coefficient of determination? Explain what it means? c. Do the signs of the coefficients make economic sense? Which of the coefficients are significant? (alpha = 0.025, df = 6, critical t-statistic = 2.447) d. If Price = 2.0, Income = 35 and Advertising = 9.5, what is the predicted quantity sold? e. Find the price and income elasticities using the information above (d). Interpret the answers. f. Explain how the above model can be used as a forecasting technique. Show how it is done.

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The regression results in Excel are below A The estimated linear equation is below Q 20586 1224P 141... View the full answer