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Below is a partial multiple regression computer

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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. 1-1406 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 1-1407 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. 1-1408 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 1-1409 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. 1-1410 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 1-1411 Chapter 01 - An Introduction to Business Statistics 88. The manufacturer of a light fixture believes that the dollars spent on advertising, the price of...
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This document was uploaded on 01/20/2014.

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