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Unformatted text preview: 1370 Chapter 01  An Introduction to Business Statistics 23. The mean square error of a multiple regression model with k independent variables and n
observations is
A. SSE / (n)
B. SSE / [(n) + (k + 1)]
C. SSE / [(n)  (k + 1)]
D. SSE / (k + 1) AACSB: Reflective Thinking
Bloom's: Comprehension
Difficulty: Medium
Learning Objective: 2
Topic: Multiple regression model 24. Which of the following is not an assumption of the multiple linear regression model?
A. Independent error terms
B. Population of error terms has a normal distribution.
C. Populations of error terms observed at different combinations of values of the independent
variable (x1, x2, xk) have equal variances.
D. The level of measurement of the data for the dependent variable is at least ordinal.
E. At any combination of values of x1, x2, xk, the population of potential error term values has
a mean equal to zero. AACSB: Reflective Thinking
Bloom's: Comprehension
Difficulty: Medium
Learning Objective: 2
Topic: Multiple regression model assumptions 25. A multiple regression analysis with 20 observations on each of three independent
variables and the dependent variable would yield ______ and _______ degrees of freedom
respectively for regression (explained) and error.
A. 3, 17
B. 3, 16
C. 4, 16
D. 3, 19
E. 3, 20 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 4
Topic: Multiple regression model 11371 Chapter 01  An Introduction to Business Statistics 26. If it is desired to include marital status in a multiple regression model by using the
categories: single, married, separated, divorced, widowed, what will be the effect on the
model?
A. One more independent variable will be included.
B. Two more independent variables will be included.
C. Three more independent variables will be included.
D. Four more independent variables will be included.
E. Five more independent variables will be included. AACSB: Reflective Thinking
Bloom's: Comprehension
Difficulty: Medium
Learning Objective: 7
Topic: Dummy variables 27. An investigator hired by a client suing for sex discrimination has developed a multiple
regression model for employee salaries for the company in question. In this multiple
regression model, the salaries are in thousands of dollars. For example, a data entry of 35 for
the dependent variable indicates a salary of $35,000. The indicator (dummy) variable for
gender is coded as X1 = 0 if male and X1 = 1 if female. The computer output of this multiple
regression model shows that the coefficient for this variable (X1) is  4.2. The t test showed
that X1 was significant at α = 0.1. This result implies that for male and female workers of the
company,
A. On the average, females earn $4200 less.
B. On the average, males earn $4200 less.
C. On the average, salaries do not differ.
D. On the average, males have 4.2 more years of experience.
E. On the average, females have 4.2 more years of experience. AACSB: Analytic
Bloom's: Application
Difficulty: Hard
Learning Objective: 7
Topic: Dummy variables 11372 Chapter 01  An Introduction to Business Statistics 28. Consider the following partial computer output for a multiple regression model. How many observations were taken?
A. 3
B. 16
C. 19
D. 20
E. 13 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 1
Topic: Multiple regression model 11373 Chapter 01  An Introduction to Business Statistics 29. Consider the following partial computer output for a multiple regression model. What is R2?
A. 31.308%
B. 76.95%
C. 87.72%
D. 72.63%
E. 23.1% AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 3
Topic: Coefficient of determination 11374 Chapter 01  An Introduction to Business Statistics 30. Consider the following partial computer output for a multiple regression model. What is the adjusted R2?
A. 31.308%
B. 76.95%
C. 87.72%
D. 72.63%
E. 23.1% AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 3
Topic: Coefficient of determination 31. The graph of the prediction equation obtained from the model
is a(n)
A. Line
B. Plane
C. Parabola
D. Exponential curve AACSB: Reflective Thinking
Bloom's: Comprehension
Difficulty: Medium
Learning Objective: 1
Topic: Multiple regression model 11375 Chapter 01  An Introduction to Business Statistics 32. In multiple regression analysis, the mean square regression divided by mean square error
yields the:
A. Standard error
B. F statistic
C. R2
D. Adjusted R2 or
E. t statistic AACSB: Reflective Thinking
Bloom's: Comprehension
Difficulty: Medium
Learning Objective: 4
Topic: Overall F test 33. In multiple regression analysis, the explained sum of squares divided by the total sum of
squares yields the:
A. Standard error
B. F statistic
C. R2
D. Adjusted R2 or
E. t statistic AACSB: Reflective Thinking
Bloom's: Comprehension
Difficulty: Medium
Learning Objective: 3
Topic: Coefficient of determination 11376 Chapter 01  An Introduction to Business Statistics 34. In multiple regression analysis, which one of the following is the appropriate notation for
error (residual)?
A.
B.
C.
D.
E. N...
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This document was uploaded on 01/20/2014.
 Winter '14

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