What proportion of the total variation in sales is explained

Reference no: EM13213585

cascade pharamacreuticals company developed the following regression model, using time-series data from the past 33 quaters, for for one of its nonprescription cold remedies: y=-1.04 + 0.24X1 - 0.27X2 Where Y = quarterly sales (in thousands pf cases) of the cold remedy X1 =Cascade's quarterly advertising (x 1,000) for the cold remedy X2 = Competitors'' advertising for the similar product (X 10,000) Here's is additional information concerning the regression model: Sb1 = 0.032 Sb2 = 0.070 R2 = 0.64 Se = 1.63 F-statics = 31.402 Durbin-Watson (d) statics = 0.4995

a. Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining sales of the cold remedy?

b. What proportion of the total variation in sales is explained by the regression equation?

c. Perform an F-test (at the 0.05 level) of the overall explanatory power of the model.

d. What additional statistical information (if any) would you find useful in the evaluation of this model?

Reference no: EM13213585

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