Question 1

The correlation coefficient resulting from a particular regression analysis was 0.25.What was the coefficient of determination?

Accepted Answer

A) 0.5 
B) -0.5 
C) 0.0625 
D) There is insufficient information to answer the question. 
E) None of the above 
A) 0.5 
B) -0.5 
C) 0.0625 
D) There is insufficient information to answer the question. 
E) None of the above

Question 2

If multicollinearity exists,then individual interpretation of the variables is questionable,but the overall model is still good for prediction purposes.

Accepted Answer

A) True 
 B)False

Question 3

Consider the regression model Y = 389.10 - 14.6X.If the r2 value is 0.657,what is the correlation coefficient?

Accepted Answer

Question 4

Which of the following statements provides the best guidance for model building?

Accepted Answer

A) If the value of r2 increases as more variables are added to the model,the variables should remain in the model,regardless of the magnitude of increase. 
B) If the value of the adjusted r2 increases as more variables are added to the model,the variables should remain in the model. 
C) If the value of r2 increases as more variables are added to the model,the variables should not remain in the model,regardless of the magnitude of the increase. 
D) If the value of the adjusted r2 increases as more variables are added to the model,the variables should not remain in the model. 
E) None of the statements provide accurate guidance. 
A) If the value of r2 increases as more variables are added to the model,the variables should remain in the model,regardless of the magnitude of increase. 
B) If the value of the adjusted r2 increases as more variables are added to the model,the variables should remain in the model. 
C) If the value of r2 increases as more variables are added to the model,the variables should not remain in the model,regardless of the magnitude of the increase. 
D) If the value of the adjusted r2 increases as more variables are added to the model,the variables should not remain in the model. 
E) None of the statements provide accurate guidance.

Question 5

What can be said about an r2 value of 0.96?

Accepted Answer

This indicates that 96% of the

Question 6

SST = SSR + ________.

Accepted Answer

SSE or sum

Question 7

List the four assumptions of the regression model.

Accepted Answer

(1)The errors are independent.

Question 8

What is the formula for r2?

Accepted Answer

SSR / SST

Question 9

The multiple regression model includes several dependent variables.

Accepted Answer

A) True 
 B)False

Question 10

The regression line minimizes the sum of the squared errors.

Accepted Answer

A) True 
 B)False

Question 11

A reference to the criterion used to select the regression line,to minimize the squared distances between the estimated straight line and the observed values is called

Accepted Answer

A) Mean square error. 
B) Sum of Squares. 
C) Maximum likelihood. 
D) R-square. 
E) Least Squares. 
A) Mean square error. 
B) Sum of Squares. 
C) Maximum likelihood. 
D) R-square. 
E) Least Squares.

Question 12

In a scatter diagram,the dependent variable is typically plotted on the horizontal axis.

Accepted Answer

A) True 
 B)False

Question 13

The regression model assumes the error terms are dependent.

Accepted Answer

A) True 
 B)False

Question 14

The multiple regression model includes several intercept terms.

Accepted Answer

A) True 
 B)False

Question 15

Summing the error values in a regression model is misleading because negative errors cancel out positive errors.

Accepted Answer

A) True 
 B)False

Question 16

The SSR indicates how much of the total variability in the dependent variable is explained by the regression model.

Accepted Answer

A) True 
 B)False

Question 17

Explain the purposes of regression models.

Accepted Answer

to understand the relationship

Question 18

A large international sales organization has collected data on the number of employees and the annual gross sales during the last 7 years.   (a)Develop a scatter diagram.
(b)Determine the correlation coefficient.
(c)Determine the coefficient of determination.
(d)Determine the least squares trend line.
(e)Determine the predicted value of sales for 2100 employees.

Accepted Answer

(a) @#IMG-DLM& (b).937
(c).878

Question 19

The variable to be predicted is the dependent variable.

Accepted Answer

A) True 
 B)False

Question 20

A dummy variable can be assigned up to three values.

Accepted Answer

A) True 
 B)False

Exam 4: Regression Models

The correlation coefficient resulting from a particular regression analysis was 0.25.What was the coefficient of determination?

If multicollinearity exists,then individual interpretation of the variables is questionable,but the overall model is still good for prediction purposes.

Consider the regression model Y = 389.10 - 14.6X.If the r2 value is 0.657,what is the correlation coefficient?

Which of the following statements provides the best guidance for model building?

What can be said about an r2 value of 0.96?

SST = SSR + ________.

List the four assumptions of the regression model.

What is the formula for r2?

The multiple regression model includes several dependent variables.

The regression line minimizes the sum of the squared errors.

A reference to the criterion used to select the regression line,to minimize the squared distances between the estimated straight line and the observed values is called

In a scatter diagram,the dependent variable is typically plotted on the horizontal axis.

The regression model assumes the error terms are dependent.

The multiple regression model includes several intercept terms.

Summing the error values in a regression model is misleading because negative errors cancel out positive errors.

The SSR indicates how much of the total variability in the dependent variable is explained by the regression model.

Explain the purposes of regression models.

The variable to be predicted is the dependent variable.

A dummy variable can be assigned up to three values.

Introduction to Quantitative Analysis

Probability Concepts and Applications

Decision Analysis

Forecasting

Inventory Control Models

Linear Programming Models: Graphical and Computer Methods

Linear Programming Applications

Transportation,assignment,and Network Models

Integer Programming,goal Programming,and Nonlinear Programming

Project Management

Waiting Lines and Queuing Theory Models

Simulation Modeling

Markov Analysis

Statistical Quality Control

Analytic Hierarchy Process

Dynamic Programming

Decision Theory and the Normal Distribution

Game Theory

Mathematical Tools: Determinants and Matrices

Calculus-Based Optimization

Linear Programming: The Simplex Method

Transportation, Assignment, and Network Algorithms

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Consider the regression model Y = 389.10 - 14.6X.If the r² value is 0.657,what is the correlation coefficient?

What can be said about an r² value of 0.96?

What is the formula for r²?