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. Newspaper Weekly Television Gross Advertising Advertising ($1,000s) ($1,000s) Revenue ($1,000s) 96 90 95 92 95 94 94 94 5.0 2.0 4.0 2.5 3.0 3.5 2.5 3.0 1.5 2.0 1.5 2.5 3.3 2.3 4.2 2.5 (a) Develop an estimated regression equation with the amount of television advertising as the independent variable. (Round your numerical values to two decimal places. Let x₁ represent the amount of television advertising in $1,000s and y represent the weekly gross revenue in $1,000s.) ŷ=

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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 Gross Revenue ($1,000s) | Television Advertising ($1,000s) | Newspaper Advertising ($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                              |

(a) Develop an estimated regression equation with the amount of television advertising as the independent variable. (Round your numerical values to two decimal places. Let \( x_1 \) represent the amount of television advertising in $1,000s and \( y \) represent the weekly gross revenue in $1,000s.)

\(\hat{y} =\) [Blank space for answer]

(b) Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables. (Round your numerical values to two decimal places. Let \( x_1 \) represent the amount of television advertising in $1,000s, \( x_2 \) represent the amount of newspaper advertising in $1,000s, and \( y \) represent the weekly gross revenue in $1,000s.)

\(\hat{y} =\) [Blank space for answer]
Transcribed Image Text: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 Gross Revenue ($1,000s) | Television Advertising ($1,000s) | Newspaper Advertising ($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 | (a) Develop an estimated regression equation with the amount of television advertising as the independent variable. (Round your numerical values to two decimal places. Let \( x_1 \) represent the amount of television advertising in $1,000s and \( y \) represent the weekly gross revenue in $1,000s.) \(\hat{y} =\) [Blank space for answer] (b) Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables. (Round your numerical values to two decimal places. Let \( x_1 \) represent the amount of television advertising in $1,000s, \( x_2 \) represent the amount of newspaper advertising in $1,000s, and \( y \) represent the weekly gross revenue in $1,000s.) \(\hat{y} =\) [Blank space for answer]
(b) Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables. (Round your numerical values to two decimal places. Let \( x_1 \) represent the amount of television advertising in $1,000s, \( x_2 \) represent the amount of newspaper advertising in $1,000s, and \( y \) represent the weekly gross revenue in $1,000s.)

\[
\hat{y} = \_\_\_
\]

(c) Is the estimated regression equation coefficient for television advertising expenditures the same in part (a) and in part (b)?

No \(\checkmark\), it is \_\_\_ in part (a) and \_\_\_ in part (b).

Interpret the coefficient in each case.

- \( \circ \) In part (a) it represents the change in revenue due to a one-unit increase in television advertising with newspaper advertising held constant. In part (b) it represents the change in revenue due to a one-unit increase in television advertising expenditure.
  
- \( \circ \) In part (a) it represents the change in revenue due to a one-unit increase in television advertising expenditure. In part (b) it represents the change in revenue due to a one-unit increase in newspaper advertising with television advertising held constant.
  
- \( \bullet \) In part (a) it represents the change in revenue due to a one-unit increase in television advertising expenditure. In part (b) it represents the change in revenue due to a one-unit increase in television advertising with newspaper advertising held constant.
  
- \( \circ \) In part (a) it represents the change in revenue due to a one-unit increase in television advertising expenditure with newspaper advertising held constant. In part (b) it represents the change in revenue due to a one-unit increase in newspaper advertising with television advertising held constant.
  
- \( \circ \) In part (a) it represents the change in revenue due to a one-unit increase in newspaper advertising expenditure with television advertising held constant. In part (b) it represents the change in revenue due to a one-unit increase in television advertising with newspaper advertising held constant.

(d) Predict weekly gross revenue (in dollars) for a week when \( \$3,100 \) is spent on television advertising and \( \$1,800 \) is spent on newspaper advertising. (Round your answer to the nearest cent.)

\[
\$ \_\_\_ \
Transcribed Image Text:(b) Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables. (Round your numerical values to two decimal places. Let \( x_1 \) represent the amount of television advertising in $1,000s, \( x_2 \) represent the amount of newspaper advertising in $1,000s, and \( y \) represent the weekly gross revenue in $1,000s.) \[ \hat{y} = \_\_\_ \] (c) Is the estimated regression equation coefficient for television advertising expenditures the same in part (a) and in part (b)? No \(\checkmark\), it is \_\_\_ in part (a) and \_\_\_ in part (b). Interpret the coefficient in each case. - \( \circ \) In part (a) it represents the change in revenue due to a one-unit increase in television advertising with newspaper advertising held constant. In part (b) it represents the change in revenue due to a one-unit increase in television advertising expenditure. - \( \circ \) In part (a) it represents the change in revenue due to a one-unit increase in television advertising expenditure. In part (b) it represents the change in revenue due to a one-unit increase in newspaper advertising with television advertising held constant. - \( \bullet \) In part (a) it represents the change in revenue due to a one-unit increase in television advertising expenditure. In part (b) it represents the change in revenue due to a one-unit increase in television advertising with newspaper advertising held constant. - \( \circ \) In part (a) it represents the change in revenue due to a one-unit increase in television advertising expenditure with newspaper advertising held constant. In part (b) it represents the change in revenue due to a one-unit increase in newspaper advertising with television advertising held constant. - \( \circ \) In part (a) it represents the change in revenue due to a one-unit increase in newspaper advertising expenditure with television advertising held constant. In part (b) it represents the change in revenue due to a one-unit increase in television advertising with newspaper advertising held constant. (d) Predict weekly gross revenue (in dollars) for a week when \( \$3,100 \) is spent on television advertising and \( \$1,800 \) is spent on newspaper advertising. (Round your answer to the nearest cent.) \[ \$ \_\_\_ \
Expert Solution
Part (a)

a) The estimated regression equation between the gross revenue with the amount of television advertising as the independent variable is given by ŷ = 88.64 + 1.61 x1  (where x1 represents the amount of television advertising in $1,000s and ŷ represents the predicted weekly gross revenue at $1,000s.)

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