The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (1) and newspaper advertising (2). Values of y, z1, and zz are expressed in thousands of dollars. Weekly Gross Television Newspaper Revenue Advertising Advertising ($1000s) ($1000s) ($1000s) 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 The estimated regression equation was ŷ = 83.23 + 2.29z1 + 1.30z2 a. What is the gross revenue expected for a week where $3,500 is spent on television (21 = 3.5) and $1,800 is spent on newspaper advertising (22 = 1.8) (to 3 decimals)? thousand b. Provide a 95% prediction interval for next week's revenue, assuming that the advertising expenditures will be allocated as in part (a) (to 2 decimals). ($ thousand, $ thousand)
The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (1) and newspaper advertising (2). Values of y, z1, and zz are expressed in thousands of dollars. Weekly Gross Television Newspaper Revenue Advertising Advertising ($1000s) ($1000s) ($1000s) 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 The estimated regression equation was ŷ = 83.23 + 2.29z1 + 1.30z2 a. What is the gross revenue expected for a week where $3,500 is spent on television (21 = 3.5) and $1,800 is spent on newspaper advertising (22 = 1.8) (to 3 decimals)? thousand b. Provide a 95% prediction interval for next week's revenue, assuming that the advertising expenditures will be allocated as in part (a) (to 2 decimals). ($ thousand, $ thousand)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Problem 1P
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Transcribed Image Text:The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (1) and newspaper advertising (*2). Values of y, æ1, and æz are expressed in thousands
of dollars.
Weekly Gross
Television
Newspaper
Revenue
Advertising
Advertising
($1000s)
($1000s)
($1000s)
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
The estimated regression equation was
ŷ = 83.23 + 2.29x1 + 1.30x2
a. What is the gross revenue expected for a week where $3,500 is spent on television (21 = 3.5) and $1,800 is spent on newspaper advertising (x2 = 1.8) (to 3 decimals)?
thousand
b. Provide a 95% prediction interval for next week's revenue, assuming that the advertising expenditures will be allocated as in part (a) (to 2 decimals).
( $
thousand, $
thousand)
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