1-20chapter stats

69 consider the following partial computer output for

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: ce 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, estimate the monthly light fixture sales and calculate the value of the residual, if the company spends $4000 on advertising, the price of the fixture is $60 and the fixture is being sold at 3 retail stores. 1-1327 Chapter 01 - An Introduction to Business Statistics 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. 1-1328 Chapter 01 - An Introduction to Business Statistics 1-1329 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. 1-1330 Chapter 01 - An Introduction to Business Statistics 1-1331 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. 1-1332 Chapter 01 - An Introduction to Business Statistics 1-1333 Chapter 01 - An Introduction to Business Statistics 88. 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...
View Full Document

Ask a homework question - tutors are online