b) Provide a 95% confidence interval (in dollars) for the mean revenue of all weeks with the expenditures listed in part (a). (Round your answers to the nearest dollar.) $ 91422 × tos 92994 c) Provide a 95% prediction interval (in dollars) for next week's revenue, assuming that the advertising expenditures will be allocated as in part (a). (Round your answers to the nearest dollar.) S 90379 X to s 94037

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A statistical program is recommended.
The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow.
Weekly
Television
Newspaper
Advertising
($1,000s)
Gross
Advertising
($1,000s)
Revenue
($1,000s)
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 owner then used multiple regression analysis to predict gross revenue (y), in thousands of dollars, as a function of television advertising (x,), in thousands of dollars, and newspaper advertising (x,), in thousands of dollars. The estimated regression equation was
ŷ = 83.2 + 2.29x, + 1.30x2.
(a) What is the gross revenue (in dollars) expected for a week when $3,000 is spent on television advertising (x, = 3) and $2,500 is spent on newspaper advertising (x, = 2.5)? (Round your answer to the nearest dollar.)
$ 93320
(b) Provide a 95% confidence interval (in dollars) for the mean revenue of all weeks with the expenditures listed in part (a). (Round your answers to the nearest dollar.)
$ 91422
x to $ 92994
(c) Provide a 95% prediction interval (in dollars) for next week's revenue, assuming that the advertising expenditures will be allocated as in part (a). (Round your answers to the nearest dollar.)
$ 90379
X to $ 94037
Transcribed Image Text:A statistical program is recommended. The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow. Weekly Television Newspaper Advertising ($1,000s) Gross Advertising ($1,000s) Revenue ($1,000s) 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 owner then used multiple regression analysis to predict gross revenue (y), in thousands of dollars, as a function of television advertising (x,), in thousands of dollars, and newspaper advertising (x,), in thousands of dollars. The estimated regression equation was ŷ = 83.2 + 2.29x, + 1.30x2. (a) What is the gross revenue (in dollars) expected for a week when $3,000 is spent on television advertising (x, = 3) and $2,500 is spent on newspaper advertising (x, = 2.5)? (Round your answer to the nearest dollar.) $ 93320 (b) Provide a 95% confidence interval (in dollars) for the mean revenue of all weeks with the expenditures listed in part (a). (Round your answers to the nearest dollar.) $ 91422 x to $ 92994 (c) Provide a 95% prediction interval (in dollars) for next week's revenue, assuming that the advertising expenditures will be allocated as in part (a). (Round your answers to the nearest dollar.) $ 90379 X to $ 94037
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