Estimate overall explanatory power of regression model use

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Reference no: EM13389792

Based on 21 months of past data, Ziggy's Drive-In has determined that the demand for its hamburgers is given by the following equation:

Q = 205.2 - 200P + 100PC + 0.5Y + 23.0A

(110.9) (35.65) (49.5) (0.117) (8.712) (standard errors)

R2 = 0.74 SEE = 18.9

where Q = number of hamburgers sold per month, in thousands

P = price of Ziggy's hamburgers, in dollars

PC = price of hamburgers for Ziggy's major competitor, in dollars

Y = income per capita in the surrounding community, thousands of dollars

A = advertising expenditures during the previous month, thousands of dollars

Currently, Ziggy charges $1.00 for its hamburgers, while its closest competitor charges $1.20. Income per capita is $20,000, while advertising was $5,000 in the preceding month.

a. Evaluate the overall explanatory power of the regression model. Use a 0.05 level of significance. State all your hypotheses and explain your results. Do not use rules of thumb. Note: You will need to calculate the F statistic to answer this question.

b. Which of the independent variables, if any, appear to be statistically significant at the 0.05 level in explaining sales? State all your hypotheses and explain your results. Do not use rules of thumb.

c. What proportion of the total variation in sales is explained by the independent variables in this regression equation? How does your answer change if you adjust your answer based on the number of observations relative to the number of variables in this equation?

d. Derive a 95% confidence interval for current sales at the present values of each variable. Do not use rules of thumb.

Reference no: EM13389792

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