| Market | Revenue | Paper Ads | TV Ads |
| Augusta | 99.3 | 3.1 | 4.1 |
| Baton Rouge | 198.0 | 6.9 | 5.8 |
| Biloxi | 120.2 | 3.5 | 2.3 |
| Birmingham | 166.4 | 4.3 | 4.3 |
| Jackson | 74.8 | 4.0 | 1.5 |
| Little Rock | 137.8 | 3.6 | 4.0 |
| Mobile | 90.8 | 5.0 | 1.5 |
| New Orleans | 237.8 | 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 |
Specifically only need help with f-h.
- Refer to the Excel “Dixie†data posted on eLearning: (18)
- Develop an estimated regression equation with the Revenueserving as the dependent variable and Paper Ads and TV Ads servingas explanatory variables. Write out this estimated equation(use the estimate values!) to explainRevenue.
- Show the residual plots where residuals are plotted againsteach explanatory variable separately. Comment on whether you canproceed with statistical inference based on what you see in theplots. (Hint: Don’t go looking for trouble!)
- Provide an interpretation for the three coefficient estimatesthat you calculated in part “aâ€. (don’t forget the intercept).
- What would your regression model predict the revenue amount tobe in a market with 0 TV Ads and 0 Paper Ads? Is this a meaningfulprediction? Answer, in a sentence, why or why not.
- Provide a 90% confidence interval for your estimate of thePaper Ads Coefficient. Interpret exactly what this 90% confidenceinterval means.
- What statistic and p-value would you use to test the specificnull hypothesis that:
Ho: b Paper Ads = bTV Ads = 0
     Do youreject or fail to reject this null hypothesis?
- g. If I asked you to consider a“backward selection†approach which only included predictors to themodel that were significant at a 99% level, then would your answerto part “a†change? If so, what would it change to?
- h. What percentage of thevariation in Revenue can be explained by the model you developed onpart “a� How much more variation does this model explain than amodel which uses only TV Ads to help predict Revenue?
