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Unformatted text preview: ing Objective: 1
Topic: Simple Linear Regression 11263 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 11264 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) 11265 Chapter 01  An Introduction to Business Statistics AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 4
Topic: Significance of the slope 11266 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 11267 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 11268 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 11269 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.
 Winter '14

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