Unformatted text preview: Difficulty: Medium
Learning Objective: 4
Topic: Multicollinearity 11496 Chapter 01  An Introduction to Business Statistics 64. ___________ is an iterative variable selection procedure that allows an independent
variable to be added to a multiple regression model in one iteration and deleted during the
next iteration?
A. Logistic regression
B. Stepwise regression
C. Quadratic regression
D. Backward regression AACSB: Reflective Thinking
Bloom's: Knowledge
Difficulty: Hard
Learning Objective: 5
Topic: Model Building 65. Stepwise regression uses a series of _____ tests during each iteration in order to determine
which independent variables should be brought into the regression model.
A. C
B. F
C. t
D. VIF AACSB: Reflective Thinking
Bloom's: Knowledge
Difficulty: Hard
Learning Objective: 5
Topic: Model Building 66. When using a multiple linear regression model, data transformations on the dependent
variable may be used in order to correct a violation of a(n) __________ of the multiple linear
regression model.
A. assumption
B. independent variables
C. autocorrelation
D. normality AACSB: Reflective Thinking
Bloom's: Knowledge
Difficulty: Medium
Learning Objective: 7
Topic: Data Transformation 11497 Chapter 01  An Introduction to Business Statistics 67. The _____________ statistic is used to test for autocorrelation among the residuals.
A. Cook's distance
B. C
C. DurbinWatson
D. R2 AACSB: Reflective Thinking
Bloom's: Knowledge
Difficulty: Medium
Learning Objective: 8
Topic: Autocorrelation 68. When the assumption of __________  residuals (error terms) is violated, the DurbinWatson statistic is used to test to determine if there is significant _____________ among the
residuals.
A. normality, probability
B. independent, probability
C. independent, autocorrelation
D. normality, autocorrelation AACSB: Reflective Thinking
Bloom's: Knowledge
Difficulty: Medium
Learning Objective: 8
Topic: Autocorrelation 69. If the absolute value of the ______________ is greater than t.005, then there is strong
evidence that the observation is an outlier with respect to its y value.
A. Cook's distance
B. C statistic
C. F
D. studentized deleted residual AACSB: Reflective Thinking
Bloom's: Knowledge
Difficulty: Medium
Learning Objective: 6
Topic: Outliers & Influential Observations 11498 Chapter 01  An Introduction to Business Statistics 70. In a regression model a(n) ______ is an observation that is well separated from the rest of
the data with respect to its y value and/or its x values.
A. Outlier
B. Influential
C. Independent
D. Dependent AACSB: Reflective Thinking
Bloom's: Knowledge
Difficulty: Easy
Learning Objective: 6
Topic: Outliers & Influential Observations 71. In converting the residual to a studentized (standardized) residual for a given observation,
the residual for the observation is divided by the residual's __________.
A. sample size
B. t value
C. standard error
D. square AACSB: Reflective Thinking
Bloom's: Knowledge
Difficulty: Hard
Learning Objective: 6
Topic: Outliers & Influential Observations 72. If successive values of the residuals are close together, then there is a(n) ___________
autocorrelation, and the value of the DurbinWatson statistic is _________.
A. negative, large
B. positive, small
C. negative, small
D. positive, large AACSB: Reflective Thinking
Bloom's: Knowledge
Difficulty: Hard
Learning Objective: 8
Topic: Autocorrelation 11499 Chapter 01  An Introduction to Business Statistics 73. If a multiple regression model has a(n) _____ statistic substantially greater than k + 1,
then it can be shown that this model has substantial bias and is undesirable.
A. C
B. F
C. Cook's distance
D. DurbinWatson AACSB: Reflective Thinking
Bloom's: Knowledge
Difficulty: Medium
Learning Objective: 5
Topic: Model Building 74. In general, a multiple regression model is considered to be desirable if the value of the C
statistic is small and the value of C is less than _____.
A. k
B. k  1
C. k + 1
D. n  k AACSB: Reflective Thinking
Bloom's: Knowledge
Difficulty: Hard
Learning Objective: 5
Topic: Model Building 11500 Chapter 01  An Introduction to Business Statistics
Essay Questions 75. Below is a partial multiple regression computer output based on a quadratic regression
model. Determine the number of observations in the sample, explained variation and the MSE.
18, 29.44, 3.997 AACSB: Analytical Skills
Bloom's: Application
Difficulty: Medium
Learning Objective: 1
Topic: Quadratic 11501 Chapter 01  An Introduction to Business Statistics 76. Below is a partial multiple regression computer output based on a quadratic regression
model. Calculate R2.
.3293 AACSB: Analytical Skills
Bloom's: Application
Difficulty: Medium
Learning Objective: 1
Topic: Quadratic 11502 Chapter 01  An Introduction to Business Statistics 77. Below is a partial multiple regression computer output based on a quadratic regression
model. Test the overall usefulness of the model at α = .05. Calculate the F statistic and make your
de...
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 Winter '14
 Frequency, Frequency distribution, Histogram, AACSB, Statistical charts and diagrams

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