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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 Rsqaured 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
 Nabavi
 Revenue

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