- 2 5 Points A Manufacturer Of A Leading Brand Of Wooden Furniture Gathered Average Monthly Sales Figures From 20 Showroom 1 (35.2 KiB) Viewed 28 times
- 2 5 Points A Manufacturer Of A Leading Brand Of Wooden Furniture Gathered Average Monthly Sales Figures From 20 Showroom 2 (35.2 KiB) Viewed 28 times
- 2 5 Points A Manufacturer Of A Leading Brand Of Wooden Furniture Gathered Average Monthly Sales Figures From 20 Showroom 3 (34.5 KiB) Viewed 28 times
2.5 points A manufacturer of a leading brand of wooden furniture gathered average monthly sales figures from 20 showrooms in Manama and estimated the following demand for its product: Q = -5.200 - 42P+20 Px +52Y 0.2A +0.250 (2002) (17.5) (6.2) (2.5) (0.09) (0.21) R2 -0.55, n = 26 and D-W=2.3 The variables and their assumed values are Q = Quantity sold per month Price of the product BD500. Px =Proof leading competitor's BD600 Y Per capita income - BD5,500. A Advertising expenditures + 10,000. C = number of consumers - 5,000. (Numbers in brackets are the standard errors of coefficients) 1 Calculate the elasticities for each variable. On this basis, discuss the relative impact that each variable has on the demand (0.5point) 2. What implications do these elasticities have for the firm's pricing policies? Do you think that this firm should cut its price to increase its sales? Explain (0.5 point) Which of the Independent variables, if any appears to be statistically significant in explaining sales of the Potato Chipa? Evaluate at the 0:05 level of significance using a two tail test. (State all your hypotheses and explain your results), (0.5 point) 4 Calculate the F.value of this regression model and evaluate the overall explanatory power of the regression model (State all your hypothesis and explain your results, use 0.05 level of significance), (0.5 point) 5. Carefully define multicolinearity, and explain how to know that it exists in a regression equation and how it affects regression analysis. What can a researcher do if heshe expects that there is multicollinearity in a regression (0.5 point)
3.5 points A manufacturer of a leading brand of wooden furniture gathered average monthly sales figures from 26 showrooms in Manama and estimated the following demand for its product Q-5,200 - 42P 20 Px.52Y+0.2A +0.250 (2.002) (17.5) (62) (25) 10.09) (0.21) R2.0,55, n = 26 and D-W-2.3 The variables and their assumed values are Q Quantity sold per month P Price of the product 30500. Px Price of leading competitor's =BD600 Y Per capita income BD5,500 A = Advertising expenditures 10,000 Ce number of consumers 5,000 Numbers in brackets are the standard errors of coefficients) 1. Calculate the elasticities for each variable. On this basis discuss the relative impact that each variable has on the demand (0.5point) 2. What implications do these elusticiles have for the firm's pricing policies? Do you think that this from should cut its price to increase its sales? Explain (0.5 point) Which of the independent variables, if any, appears to be statistically significant in explaining anles of the Potato Chipo? Evaluate at the 0.05 level of significance, using a two- Lail fest. (Stato all your hypotheses and explain your results), (0.5 point) 1. Calculate the F.value of this regression model and evaluate the overall explanatory power of the regression model (State all your hypotheses and explain your retuits, un 0.05 level of significance) (0.5 point) 5. Carefully define multicolinearity, and explain how to know that it exists in a regression equation and how it affects regression analysis What can a researcher do if he/she expects that there is multicolinearity in a regression? (0.5 point)