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Develop an estimated regression equation

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Reference no: EM132887784

Question:Atlanta 233.3 3.9 6.5

Augusta 99.3 3.1 4.1

Baton Rouge 198.0 6.9 5.8Biloxi 120.2 3.5 2.3

Market Revenue Paper Ads TV Ads

Birmingham 166.4 4.3 4.3

Chattanooga 136.5 3.9 3.1

Jackson 74.8 4.0 1.5

Little Rock 137.8 3.6 4.0

Mobile 90.8 5.0 1.5

New Orleans 299.1 5.0 8.4

Savannah 147.0 4.4 2.7

Shreveport 56.5 3.0 3.0

Tunica 78.8 1.9 4.4

Vicksburg 100.5 2.7 2.9

1. Refer to the Excel "Southern" data posted on eLearning:

a. Develop an estimated regression equation with the Revenue serving as the dependent variable and Paper Ads and TV Ads serving as explanatory variables. Write out this estimated equation (use the estimate values!) to explain Revenue. Do not use generic labels like 'x1' when you can use problem-specific labels.

b. Show the residual plots where residuals are plotted against each explanatory variable separately. Comment on whether you can proceed with statistical inference based on what you see in the plots. (Hint: Don't go looking for trouble!)

c. Provide an interpretation for the three coefficient estimates that you calculated in part "a". (don't forget the intercept).

d. What would your regression model predict the revenue amount to be in a market with 0 TV Ads and 0 Paper Ads? Is this a meaningful prediction? Answer, in a sentence, why or why not.

e. Provide a 90% confidence interval for your estimate of the Paper Ads Coefficient. Interpret exactly what this 90% confidence interval means.

f. What statistic and p-value would you use to test the specific null hypothesis that:

Ho: b Paper Ads = b TV Ads = 0

Do you reject or fail to reject this null hypothesis?

g. If I asked you to consider a "backward selection" approach which only included predictors to the model that were significant at a 99% level, then would your answer to part "a" change? If so, what would it change to?

h. What percentage of the variation in Revenue can be explained by the model you developed on part "a"? How much more variation does this model explain than a model which uses only TV Ads to help predict Revenue?

Reference no: EM132887784

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