The following data describes weekly gross revenue ($1000s), television advertising expenditures ($1000s), and newspaper advertising expenditures ($1000s) for Showtime Movie Theaters. Weekly Gross Revenue ($1000s) 99 90 95 92 95 94 94 94 2.84 Revenue = X 81.73 TVAdv+ + b. Choose the correct plot of the standardized residuals against ŷ. a. Find an estimated regression equation relating weekly gross revenue to television advertising expenditures and newspaper advertising expenditures (to 21 decimals). Television Advertising ($1000s) 5.0 2.0 4.0 2.5 3.0 3.5 2.5 3.0 1.29 Newspaper Advertising ($1000s) 1.5 2.0 1.5 2.5 3.3 2.3 4.2 2.5 News Adv

Practical Management Science
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Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
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The following data describes weekly gross revenue ($1000s), television advertising expenditures ($1000s), and newspaper advertising expenditures ($1000s)
for Showtime Movie Theaters.
×
Weekly Gross
+
Revenue
($1000s)
99
90
95
92
95
94
94
94
a. Find an estimated regression equation relating weekly gross revenue to television advertising expenditures and newspaper advertising expenditures (to 2
decimals).
2.84
Television
Advertising
($1000s)
5.0
2.0
4.0
2.5
3.0
3.5
2.5
3.0
Revenue =
81.73
1.29 News Adv
TV Adv +
b. Choose the correct plot of the standardized residuals against ĝ.
Newspaper
Advertising
($1000s)
1.5
2.0
1.5
2.5
3.3
2.3
4.2
2.5
Transcribed Image Text:The following data describes weekly gross revenue ($1000s), television advertising expenditures ($1000s), and newspaper advertising expenditures ($1000s) for Showtime Movie Theaters. × Weekly Gross + Revenue ($1000s) 99 90 95 92 95 94 94 94 a. Find an estimated regression equation relating weekly gross revenue to television advertising expenditures and newspaper advertising expenditures (to 2 decimals). 2.84 Television Advertising ($1000s) 5.0 2.0 4.0 2.5 3.0 3.5 2.5 3.0 Revenue = 81.73 1.29 News Adv TV Adv + b. Choose the correct plot of the standardized residuals against ĝ. Newspaper Advertising ($1000s) 1.5 2.0 1.5 2.5 3.3 2.3 4.2 2.5
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