5 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 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 Dont go looking for trouble ) Provide an interpretation for the three coefficient estimates that you calculated in part a (dont forget the intercept) 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 Provide a 90 confidence interval for your estimate of the Paper Ads Coefficient Interpret exactly what this 90 confidence interval means What statistic and p value would you use to test the specific null hypothesis that b Paper Ads b TV Ads 0 Do you reject or fail to reject this null hypothesis 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 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 E F G All measures are in $100s 1 Market 2 Augusta 3 Baton Rouge 4 Biloxi 5 Birmingham 6 Jackson 7 Little Rock 3 Mobile 9 New Orleans 0 Savannah 1 Shreveport 2 Tunica 3 Vicksburg B C D Revenue Paper Ads TV Ads 99 3 3 1 4 1 198 0 6 9 5 8 120 2 3 5 2 3 166 4 4 3 4 3 74 8 4 0 1 5 137 8 3 6 4 0 90 8 5 0 1 5 237 8 5 0 8 4 147 0 4 4 2 7 56 5 3 0 3 0 78 8 1 9 4 4 100 5 2 7 2 9 4 5 E F G All measures are in $100s 1 Market 2 Augusta 3 Baton Rouge 4 Biloxi 5 Birmingham 6 Jackson 7 Little Rock 3 Mobile 9 New Orleans 0 Savannah 1 Shreveport 2 Tunica 3 Vicksburg B C D Revenue Paper Ads TV Ads 99 3 3 1 4 1 198 0 6 9 5 8 120 2 3 5 2 3 166 4 4 3 4 3 74 8 4 0 1 5 137 8 3 6 4 0 90 8 5 0 1 5 237 8 5 0 8 4 147 0 4 4 2 7 56 5 3 0 3 0 78 8 1 9 4 4 100 5 2 7 2 9 4 5

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5. Develop an estimated regression equation with the Revenue serving as the dependent variable and Paper Ads and TV Ads serving as explanatory variables. Write

1. 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.
2. 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: Dont go looking for trouble!)
3. Provide an interpretation for the three coefficient estimates that you calculated in part a. (dont forget the intercept).
4. 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.
5. Provide a 90% confidence interval for your estimate of the Paper Ads Coefficient. Interpret exactly what this 90% confidence interval means.
6. What statistic and p-value would you use to test the specific null hypothesis that:
b _{Paper Ads} = b _{TV Ads} = 0

Do you reject or fail to reject this null hypothesis?

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?
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?

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E F G *All measures are in $100s 1 Market 2 Augusta 3 Baton Rouge 4 Biloxi 5 Birmingham 6 Jackson 7 Little Rock 3 Mobile 9 New Orleans 0 Savannah 1 Shreveport 2 Tunica 3 Vicksburg B C D Revenue Paper Ads TV Ads 99.3 3.1 4.1 198.0 6.9 5.8 120.2 3.5 2.3 166.4 4.3 4.3 74.8 4.0 1.5 137.8 3.6 4.0 90.8 5.0 1.5 237.8 5.0 8.4 147.0 4.4 2.7 56.5 3.0 3.0 78.8 1.9 4.4 100.5 2.7 2.9 4. 5 E F G *All measures are in $100s 1 Market 2 Augusta 3 Baton Rouge 4 Biloxi 5 Birmingham 6 Jackson 7 Little Rock 3 Mobile 9 New Orleans 0 Savannah 1 Shreveport 2 Tunica 3 Vicksburg B C D Revenue Paper Ads TV Ads 99.3 3.1 4.1 198.0 6.9 5.8 120.2 3.5 2.3 166.4 4.3 4.3 74.8 4.0 1.5 137.8 3.6 4.0 90.8 5.0 1.5 237.8 5.0 8.4 147.0 4.4 2.7 56.5 3.0 3.0 78.8 1.9 4.4 100.5 2.7 2.9 4. 5