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Unformatted text preview: ting of monthly tire sales (in thousands of tires)
and monthly advertising expenditures (in thousands of dollars). The simple linear regression
equation is
= 3 + 1X. The dealer randomly selects one of the six observations with a
monthly sales value of 8000 tires and monthly advertising expenditures of $7000. Calculate
the value of the residual for this observation.
A. 1
B. 2
C. 2
D. 1
= 3 + 1(7) = 10
e = 8  10 = 2 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 9
Topic: Residual analysis 11270 Chapter 01  An Introduction to Business Statistics 117. 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). Residuals are calculated for
all of the randomly selected six months and ordered from smallest to largest.
Determine the normal score for the smallest residual.
A. .1053
B. 1.25
C. 1053
D. 1.25 AACSB: Analytic
Bloom's: Application
Difficulty: Easy
Learning Objective: 9
Topic: Residual analysis 11271 Chapter 01  An Introduction to Business Statistics 118. 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). Residuals are calculated for
all of the randomly selected six months and ordered from smallest to largest.
Determine the normal score for the third residual in the ordered array.
A. 0.421
B. 0.2
C. 0.2
D. 0.421 AACSB: Analytic
Bloom's: Application
Difficulty: Easy
Learning Objective: 9
Topic: Residual analysis 11272 Chapter 01  An Introduction to Business Statistics 119. A data set with 7 observations yielded the following. Use the simple linear regression
model.
= 21.57
= 68.31
= 188.9
= 5,140.23
= 590.83
SSE = 1.06
Find the estimated slope.
A. 12.36
B. 3.13
C. 4.745
D. 8.70 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 2
Topic: Simple Linear Regression 11273 Chapter 01  An Introduction to Business Statistics 120. A data set with 7 observations yielded the following. Use the simple linear regression
model.
= 21.57
= 68.31
= 188.9
= 5,140.23
= 590.83
SSE = 1.06
Find the estimated yintercept.
A. 4.745
B. 12.36
C. 9.76
D. 3.08 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 2
Topic: Simple Linear Regression 11274 Chapter 01  An Introduction to Business Statistics 121. A data set with 7 observations yielded the following. Use the simple linear regression
model.
= 21.57
= 68.31
= 188.9
= 5,140.23
= 590.83
SSE = 1.06
Calculate the standard error.
A. .212
B. .1514
C. .389
D. .4604 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 3
Topic: Simple Linear Regression 11275 Chapter 01  An Introduction to Business Statistics 122. A data set with 7 observations yielded the following. Use the simple linear regression
model.
= 21.57
= 68.31
= 188.9
= 5,140.23
= 590.83
SSE = 1.06
Find the rejection point for the t statistic (
A. 2.015, reject null hypothesis
B. 13.993, reject null hypothesis
C. 1.358, reject null hypothesis
D. 36.460, reject null hypothesis = .05). Test H0: β1 ≤ 0 vs. Ha: β1 > 0. AACSB: Analytic
Bloom's: Application
Difficulty: Hard
Learning Objective: 4
Topic: Significance of the slope 11276 Chapter 01  An Introduction to Business Statistics 123. A data set with 7 observations yielded the following. Use the simple linear regression
model.
= 21.57
= 68.31
= 188.9
= 5,140.23
= 590.83
SSE = 1.06
Determine the 95% confidence interval for the average value of Y when x = 3.25.
A. (27.31 28.25)
B. (26.51 29.05)
C. (1.98 4.52)
D. (2.78 3.72) AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 5
Topic: Confidence & predication intervals 11277 Chapter 01  An Introduction to Business Statistics 124. A data set with 7 observations yielded the following. Use the simple linear regression
model.
= 21.57
= 68.31
= 188.9
= 5,140.23
= 590.83
SSE = 1.06
Calculate the correlation coefficient.
A. .111
B. .334
C. .974
D. .987 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 6
Topic: Correlation 11278 Chapter 01  An Introduction to Business Statistics 125. A data set with 7 observations yielded the following. Use the simple linear regression
model.
= 21.57
= 68.31
= 188.9
= 5,140.23
= 590.83
SSE = 1.06
Calculate the coefficient of determination.
A. .111
B. .334
C. .974
D. .987 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 6
Topic: Coefficient of determination 11279 Chapter 01  An Introduction to Business Statistics 126. Use the least sq...
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This document was uploaded on 01/20/2014.
 Winter '14

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