Unformatted text preview: 85. The manufacturer of a light fixture believes that the dollars spent on advertising, the price
of the fixture and the number of retail stores selling the fixture in a particular month, influence
the light fixture sales. The manufacturer randomly selects 10 months and collects the
following data: The sales are in thousands of units per month, the advertising is given in hundreds of dollars
per month, and the price is the unit retail price for the particular month. Using MINITAB the
following computer output is obtained.
The regression equation is
Sales = 31.0 + 0.820 Advertising  0.325 Price + 1.84 Stores S = 5.465 R  Sq = 96.7% R  Sq(adj) = 95.0%
Analysis of Variance Based on the multiple regression model given above, the point estimate of the monthly light
fixture sales corresponding to second sample data is 49.82 or 49,820 units. This point estimate
is calculated based on the assumption that the company spends $4000 on advertising, the price
of the fixture is $60 and the fixture is being sold at 3 retail stores. Additional information
related to this point estimate is given below. Determine the 95% confidence interval for this point estimate and interpret its meaning. 11406 Chapter 01  An Introduction to Business Statistics 41.183 to 58.457. We are 95% confident that the monthly unit sales is estimated to be at least
41,182 fixtures and at most 58,458 fixtures. This is based on the assumption that the company
spends an average of $4000 per month on advertising, the price of the fixture averages $60
and the fixture is being sold at an average of 3 retail stores in a given month. AACSB: Analytic
Bloom's: Application
Difficulty: Hard
Learning Objective: 6
Topic: Confidence & prediction intervals 11407 Chapter 01  An Introduction to Business Statistics 86. The manufacturer of a light fixture believes that the dollars spent on advertising, the price
of the fixture and the number of retail stores selling the fixture in a particular month, influence
the light fixture sales. The manufacturer randomly selects 10 months and collects the
following data: The sales are in thousands of units per month, the advertising is given in hundreds of dollars
per month, and the price is the unit retail price for the particular month. Using MINITAB the
following computer output is obtained.
The regression equation is
Sales = 31.0 + 0.820 Advertising  0.325 Price + 1.84 Stores S = 5.465 R  Sq = 96.7% R  Sq(adj) = 95.0%
Analysis of Variance Based on the multiple regression model given above, the point estimate of the monthly light
fixture sales corresponding to second sample data is 49.82 or 49,820 units. This point estimate
is calculated based on the assumption that the company spends $4000 on advertising, the price
of the fixture is $60 and the fixture is being sold at 3 retail stores. Additional information
related to this point estimate is given below. Calculate the 95% prediction interval for this point estimate. 11408 Chapter 01  An Introduction to Business Statistics 33.9 to 65.74. AACSB: Analytic
Bloom's: Application
Difficulty: Hard
Learning Objective: 6
Topic: Confidence & prediction intervals 11409 Chapter 01  An Introduction to Business Statistics 87. The manufacturer of a light fixture believes that the dollars spent on advertising, the price
of the fixture, and the number of retail stores selling the fixture in a particular month,
influence the light fixture sales. The manufacturer randomly selects 10 months and collects
the following data: The sales are in thousands of units per month, the advertising is given in hundreds of dollars
per month, and the price is the unit retail price for the particular month. Using MINITAB the
following computer output is obtained.
The regression equation is
Sales = 31.0 + 0.820 Advertising  0.325 Price + 1.84 Stores S = 5.465v R  Sq = 96.7% R  Sq(adj) = 95.0%
Analysis of Variance Based on the multiple regression model given above, the point estimate of the monthly light
fixture sales corresponding to second sample data is 49.82 or 49,820 units. This point estimate
is calculated based on the assumption that the company spends $4000 on advertising, the price
of the fixture is $60 and the fixture is being sold at 3 retail stores. Additional information
related to this point estimate is given below. The 95% prediction interval for the point estimate given above is from 33.9 to 65.74. Interpret
the meaning of this interval. 11410 Chapter 01  An Introduction to Business Statistics We are 95% confident that the actual monthly unit sales is estimated to be at least 33,900
fixtures and at most 65,740 fixtures. This is based on the assumption that, in a particular
month, the company spends $4000 on advertising, the price of the fixture is $60 and the
fixture is being sold at 3 retail stores. AACSB: Analytic
Bloom's: Analysis
Difficulty: Hard
Learning Objective: 6
Topic: Multiple regression model 11411 Chapter 01  An Introduction to Business Statistics 88. The manufacturer of a light fixture believes that the dollars spent on advertising, the price
of...
View
Full Document
 Winter '14
 Frequency, Frequency distribution, Histogram, AACSB, Statistical charts and diagrams

Click to edit the document details