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Unformatted text preview: Data Page 1 96 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5 2.5 95 3.0 3.3 94 3.5 2.3 94 2.5 4.2 94 3.0 2.5 In this problem, since we are predicting revenues, it should be treated as Y. The other two variables, Columns B and C, are independent variables. Part a asks for a simple regression Part b asks for multiple regression Part c asks to compare results of part a and part b. In particular, you are asked to compare the slope coefficient for TV advertising dollars from the simple and multiple regression results. Part d asks for you to plug numbers in the multiple regression model (of part b) and estimate weekly revenues. Notice that we must use Adjusted R-sqaured in Multiple regression. The explanation is on page 344 of your text. Weekly Gross Revenue ($1000s) Televison Advertising ($1000s) Newspaper Advertising ($1000s) part a Page 2 Using TV Adverstising as X variable SUMMARY OUTPUT Regression Statistics Multiple R 0.8078074081 R Square 0.6525528086 Approximately 65% of variability in revenues is accounted for and explained by TV advertising...
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This note was uploaded on 11/13/2011 for the course MBA 522 taught by Professor Nabavi during the Spring '08 term at Bellevue.
- Spring '08