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Conduct t-test for statistical significance of each variable

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Reference no: EM132995327

One of the leading TV producers has estimated the following demand equation after analyzing 36 regional markets:

Q = + 25,000 - 50P + 25A + 20 cP

- 40 CA

+ 120 I

(12000) (22.2) (12) (8.5) (52) (55)

R 2 = 0.82 F = 32.26

The variables and their assumed values are

Q = Quantity

P = Price of the basic Model = 600 (dollars)

A = Advertising Expenditures = 100 (thousand dollars)

CP = Average price of the competitor's product = 700 (dollars)

CA = competitor's advertising expenditures = 80 (thousand dollars)

I = per capita income = 50 (thousand dollars)

Problem a. Compute the elasticities for each variable. On this basis, discuss the relative impact that each variable has on the demand. What implications do these results have for the firm's marketing, pricing, and production policies?

Problem b. What would be the effect of a 6 unit increase in the competitor's advertising expenditures?

Problem c. What would be the change in your advertising expenditures to offset your competitor's strategy?

Problem d. Conduct a t-test for the statistical significance of each variable. Discuss the results of the t-tests in light of the policy implications mentioned.

Problem e. What proportion of the variation in sales is explained by the independent variables in the equation? How confident are you about this answer? Explain conducting an F-test.

Reference no: EM132995327

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