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Regression model, F-test

Genzero Pharmaceuticals developed the following regression model based on time series data from the past 33 quarters, for one of its non-prescription cold remedies:

Where Y = quarterly sales (in thousands of cases) of the cold remedy.
= Genzero's quarterly advertising (x$1,000) for the cold remedy.
= Competitors' advertising for similar products (x$10,000).

Here is additional information from the regression model:
= 0.032 = 0.070 R-square = 0.64
= 1.63 F-stat = 31.402 Durbin-Watson (d) stat = .4995

a.) Which of the independent variables (if any) appear to be statistically significant (at the 0.05 level) in explaining sales?
b.) What proportion of the total variation in sales is explained by the regression equation?
c.) Perform an F-test (at the .05 level) of the overall explanatory power of the model.
d.) How do the results in part d affect your answers to parts a, b, and c?
e.) What additional statistical information (if any) would you find useful in the evaluation of this model?

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