Question 1

When the independent variables are correlated with each other, ________ is said to exist.

Accepted Answer

multicolli

Question 2

In any regression model, there is an implicit assumption that a relationship exists between the variables.

Accepted Answer

A) True 
 B)False

Question 3

Which of the following is not an assumption of the regression model?

Accepted Answer

A)  The errors are independent. 
B)  The errors are normally distributed. 
C)  The errors have constant variance. 
D)  The mean of the errors is zero. 
E)  The errors should have a standard deviation equal to one. 
A)  The errors are independent. 
B)  The errors are normally distributed. 
C)  The errors have constant variance. 
D)  The mean of the errors is zero. 
E)  The errors should have a standard deviation equal to one.

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

An air conditioning and heating repair firm conducted a study to determine if the average outside temperature could be used to predict the cost of an electric bill for homes during the winter months in Houston, Texas. The resulting regression equation was:
Y = 227.19 - 1.45X, where Y = monthly cost, X = average outside air temperature
(a) If the temperature averaged 48 degrees during December, what is the forecasted cost of December's electric bill?
(b) If the temperature averaged 38 degrees during January, what is the forecasted cost of January's electric bill?

Accepted Answer

(a) $227.19 - $1.45(

Question 6

The problem of nonconstant error variance is detected in residual analysis by which of the following?

Accepted Answer

A)  a cone pattern 
B)  an arched pattern 
C)  a random pattern 
D)  an increasing pattern 
E)  a decreasing pattern 
A)  a cone pattern 
B)  an arched pattern 
C)  a random pattern 
D)  an increasing pattern 
E)  a decreasing pattern

Question 7

Describe a residual plot.

Accepted Answer

A residual plot is a plot of t

Question 8

For each qualitative variable, he number of dummy variables must equal ________ the number of categories of the qualitative variable.

Accepted Answer

The answer of For each qualitative variable, he number of...

Question 9

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

Accepted Answer

A) True 
 B)False

Question 10

The problem of a nonlinear relationship is detected in residual analysis by which of the following?

Accepted Answer

A)  a cone pattern 
B)  an arched pattern 
C)  a random pattern 
D)  an increasing pattern 
E)  a decreasing pattern 
A)  a cone pattern 
B)  an arched pattern 
C)  a random pattern 
D)  an increasing pattern 
E)  a decreasing pattern

Question 11

What is the difference between simple linear regression models and multiple regression models?

Accepted Answer

Multiple regression

Question 12

In regression, there is random error that can be predicted.

Accepted Answer

A) True 
 B)False

Question 13

An air conditioning and heating repair firm conducted a study to determine if the average outside temperature could be used to predict the cost of an electric bill for a home during the winter months in Richmond, VA. It was determined that a quadratic model could be used and the following prediction equation was established:
Y = $1557.76 - 55.05X1 + 0.56X2
where Y = monthly cost, X1 = average temperature, and X2 = average temperature2
(a) If December has an average temperature of 43 degrees what is the forecasted monthly electric bill?
(b) If January has an average temperature of 40 degrees what is the forecasted monthly electric bill?

Accepted Answer

(a) $1557.76 - 55.05

Question 14

SST = SSR + ________.

Accepted Answer

SSE or sum

Question 15

The null hypothesis in the F-test is that there is a linear relationship between the X and Y variables.

Accepted Answer

A) True 
 B)False

Question 16

If computing a causal linear regression model of Y = a + bX and the resultant r2 is very near zero, then one would be able to conclude that

Accepted Answer

A)  Y = a + bX is a good forecasting method. 
B)  Y = a + bX is not a good forecasting method. 
C)  a multiple linear regression model is a good forecasting method for the data. 
D)  a multiple linear regression model is not a good forecasting method for the data. 
E)  None of the above 
A)  Y = a + bX is a good forecasting method. 
B)  Y = a + bX is not a good forecasting method. 
C)  a multiple linear regression model is a good forecasting method for the data. 
D)  a multiple linear regression model is not a good forecasting method for the data. 
E)  None of the above

Question 17

A large department store has collected the following monthly data on lost sales revenue due to theft and the number of security guard hours on duty:   (a) Determine the least squares regression equation.
(b) Using the results of part (a), find the estimated lost sales revenues if the total number of security guard hours is 800.
(c) Calculate the coefficient of correlation.
(d) Calculate the coefficient of determination.

Accepted Answer

(a) least squares equation: Y

Question 18

The ________ measures the variability in Y about the regression line.

Accepted Answer

SSE or sum

Question 19

The correlation coefficient has values between −1 and +1.

Accepted Answer

A) True 
 B)False

Question 20

List four pitfalls of regression.

Accepted Answer

If the assumptions are not met, the stat

When the independent variables are correlated with each other, ________ is said to exist.

In any regression model, there is an implicit assumption that a relationship exists between the variables.

Which of the following is not an assumption of the regression model?

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

The problem of nonconstant error variance is detected in residual analysis by which of the following?

Describe a residual plot.

For each qualitative variable, he number of dummy variables must equal ________ the number of categories of the qualitative variable.

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

The problem of a nonlinear relationship is detected in residual analysis by which of the following?

What is the difference between simple linear regression models and multiple regression models?

In regression, there is random error that can be predicted.

SST = SSR + ________.

The null hypothesis in the F-test is that there is a linear relationship between the X and Y variables.

If computing a causal linear regression model of Y = a + bX and the resultant r² is very near zero, then one would be able to conclude that

The ________ measures the variability in Y about the regression line.

The correlation coefficient has values between −1 and +1.

List four pitfalls of regression.

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 and Assignment Models

Integer Programming, Goal Programming, and Nonlinear Programming

Network Models

Project Management

Waiting Lines and Queuing Theory Models

Simulation Modeling

Markov Analysis

Statistical Quality Control

Filters

Exam 4: Regression Models

When the independent variables are correlated with each other, ________ is said to exist.

In any regression model, there is an implicit assumption that a relationship exists between the variables.

Which of the following is not an assumption of the regression model?

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

The problem of nonconstant error variance is detected in residual analysis by which of the following?

Describe a residual plot.

For each qualitative variable, he number of dummy variables must equal ________ the number of categories of the qualitative variable.

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

The problem of a nonlinear relationship is detected in residual analysis by which of the following?

What is the difference between simple linear regression models and multiple regression models?

In regression, there is random error that can be predicted.

SST = SSR + ________.

The null hypothesis in the F-test is that there is a linear relationship between the X and Y variables.

If computing a causal linear regression model of Y = a + bX and the resultant r2 is very near zero, then one would be able to conclude that

The ________ measures the variability in Y about the regression line.

The correlation coefficient has values between −1 and +1.

List four pitfalls of regression.

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 and Assignment Models

Integer Programming, Goal Programming, and Nonlinear Programming

Network Models

Project Management

Waiting Lines and Queuing Theory Models

Simulation Modeling

Markov Analysis

Statistical Quality Control

Filters

If computing a causal linear regression model of Y = a + bX and the resultant r² is very near zero, then one would be able to conclude that