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645 2776 failed to reject h0 1 1259 chapter 01 an

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Unformatted text preview: ing Objective: 1 Topic: Simple Linear Regression 1-1263 Chapter 01 - An Introduction to Business Statistics 111. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression equation of the least squares line is = 3 + 1x. = 24 = 124 = 42 = 338 = 196 MSE = 4 Use the least squares regression equation and estimate the monthly tire sales when advertising expenditures is $4000. A. 4000 tires B. 1000 tires C. 3000 tires D. 7000 tires AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 1 Topic: Simple Linear Regression 1-1264 Chapter 01 - An Introduction to Business Statistics 112. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression equation of the least squares line is = 3 + 1x. = 24 = 124 = 42 = 338 = 196 MSE = 4 Using the sums of the squares given above, determine the 95% confidence interval for the slope. A. (1.951 4.049) B. (-4.552 6.552) C. (-.0492 2.0492) D. (0.259 1.741) 1-1265 Chapter 01 - An Introduction to Business Statistics AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 4 Topic: Significance of the slope 1-1266 Chapter 01 - An Introduction to Business Statistics 113. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression equation of the least squares line is = 3 + 1x. = 24 = 124 = 42 = 338 = 196 MSE = 4 Using the sums of the squares given above, determine the 90% confidence interval for the mean value of monthly tire sales when the advertising expenditure is $5000. A. (3.32 12.68) B. (3.74 12.26) C. (6.62 9.38) D. (6.08 9.92) Ŷ = 3 + 1(5) = 8 S = √MSE = √4 = 2 Distance Value = 1/6 + ((5 - 4)2/(124 - (242/6)) = .20238 t.05,4 = 2.132 8 ± (2.132) (2) (√.20238) = 6.08, 9.92 AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 5 Topic: Confidence & predication intervals 1-1267 Chapter 01 - An Introduction to Business Statistics 114. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of tire sales (in thousands of tires) and advertising expenditures (in thousands of dollars). Based on the data set with 6 observations, the simple linear regression equation of the least squares line is = 3 + 1x. = 24 = 124 = 42 = 338 = 196 MSE = 4 Using the sums of the squares given above, determine the 90% prediction interval for an individual month's tire sales when the advertising expenditure is $5000. A. (3.32 12.68) B. (3.74 12.26) C. (6.62 9.38) D. (6.08 9.92) Ŷ = 3 + 1(5) = 8 S = √MSE = √4 = 2 Distance Value = 1/6 + ((5 - 4)2/(124 - (242/6)) = .20238 t.05,4 = 2.132 8 ± (2.132) (2) (√1 + .20238) = 3.32, 12.68 AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 5 Topic: Confidence & predication intervals 1-1268 Chapter 01 - An Introduction to Business Statistics 115. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of monthly tire sales (in thousands of tires) and monthly advertising expenditures (in thousands of dollars). The simple linear regression equation is = 3 + 1X and sample correlation coefficient (r2) = .6364. Test to determine if there is a significant correlation between the monthly tire sales and monthly advertising expenditures. Use H0: ρ = 0 vs. HA: ρ ≠ 0 at α = .05. A. Reject the null hypothesis B. Fail to reject the null hypothesis Failed to reject H0, and there is no significant correlation. AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 7 Topic: Correlation 1-1269 Chapter 01 - An Introduction to Business Statistics 116. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consis...
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This document was uploaded on 01/20/2014.

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