Question 1

The regression line minimizes the sum of the ________.

Accepted Answer

squared errors

Question 2

Both the p-value for the F-test and r2 can be interpreted the same with multiple regression models as they are with simple linear models.

Accepted Answer

A) True 
 B)False  True

Question 3

The adjusted r2 will always increase as additional variables are added to the model.

Accepted Answer

A) True 
 B)False  False

Question 4

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 5

The coefficient of determination resulting from a particular regression analysis was 0.85.What was the correlation coefficient,assuming a positive linear relationship?

Accepted Answer

A) 0.5 
B) -0.5 
C) 0.922 
D) There is insufficient information to answer the question. 
E) None of the above 
A) 0.5 
B) -0.5 
C) 0.922 
D) There is insufficient information to answer the question. 
E) None of the above

Question 6

In regression,a binary variable is also called an indicator variable.

Accepted Answer

A) True 
 B)False

Question 7

Bob White is conducting research on monthly expenses for medical care,including over-the-counter medicine.His dependent variable is monthly expenses for medical care while his independent variable is number of family members.Below is his Excel output.   (a)What is the prediction equation?
(b)Based on his model,each additional family member increases the predicted costs by how much?
(c)Based on the significance F-test,is this model a good prediction equation?
(d)What percent of the variation in medical expenses is explained by the size of the family?
(e)Can the null hypothesis that the slope is zero be rejected? Why or why not?
(f)What is the value of the correlation coefficient?

Accepted Answer

(a)Y = 110.47 + 16.83X
(b)$16.83
(c)Yes,

Question 8

A dummy variable is also called a(n)

Accepted Answer

A) indicator variable. 
B) dependent variable. 
C) continuous variable. 
D) response variable. 
E) None of the above 
A) indicator variable. 
B) dependent variable. 
C) continuous variable. 
D) response variable. 
E) None of the above

Question 9

The ________ measures the total variability in Y about the mean.

Accepted Answer

SST or sum

Question 10

The coefficients of each independent variable in a multiple regression model represent slopes.

Accepted Answer

A) True 
 B)False

Question 11

The SST measures the total variability in the dependent variable about the regression line.

Accepted Answer

A) True 
 B)False

Question 12

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(4

Question 13

Another name for the "Multiple R" that is given in Excel is ________.

Accepted Answer

correlation coeffici

Question 14

One purpose of regression is to predict the value of one variable based on the other variable.

Accepted Answer

A) True 
 B)False

Question 15

A healthcare executive is using regression to predict total revenues.She is deciding whether or not to include both patient length of stay and insurance type in her model.Her first regression model only included patient length of stay.The resulting r2 was .83,with an adjusted r2 of .82 and her level of significance was .003.In the second model,she included both patient length of stay and insurance type.The r2 was .84 and the adjusted r2 was .80 for the second model and the level of significance did not change.Which of the following statements is true?

Accepted Answer

A) The second model is a better model. 
B) The first model is a better model. 
C) The r2 increased when additional variables were added because these variables significantly contribute to the prediction of total revenues. 
D) The adjusted r2 always increases when additional variables are added to the model. 
E) None of the above statements are true. 
A) The second model is a better model. 
B) The first model is a better model. 
C) The r2 increased when additional variables were added because these variables significantly contribute to the prediction of total revenues. 
D) The adjusted r2 always increases when additional variables are added to the model. 
E) None of the above statements are true.

Question 16

The standard error of the estimate is also called the variance of the regression.

Accepted Answer

A) True 
 B)False

Question 17

The errors in a regression model are assumed to have zero variance.

Accepted Answer

A) True 
 B)False

Question 18

If every point lies on the regression line,r2 = ________.

Accepted Answer

Question 19

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 20

Bob White is conducting research on monthly expenses for medical care,including over the counter medicine.His dependent variable is monthly expenses for medical care while his independent variables are number of family members and insurance type (government funded,private insurance and other).He has coded insurance type as the following:
X2 = 1 if government funded,X3 = 1 if private insurance
Below is his Excel output.   (a)What is the prediction equation?
(b)Based on the significance F-test,is this model a good prediction equation?
(c)What percent of the variation in medical expenses is explained by the independent variables?
(d)Based on his model,what are the predicted monthly expenses for a family of four with private insurance?
(e)Based on his model,what are the predicted monthly expenses for a family of two with government funded insurance?
(f)Based on his model,what are the predicted monthly expenses for a family of five with no insurance?

Accepted Answer

(a)Y = 144.91 + 11.63X₁ - 13.70 X₂ - 9.11X

The regression line minimizes the sum of the ________.

Both the p-value for the F-test and r² can be interpreted the same with multiple regression models as they are with simple linear models.

The adjusted r² will always increase as additional variables are added to the model.

The coefficient of determination resulting from a particular regression analysis was 0.85.What was the correlation coefficient,assuming a positive linear relationship?

In regression,a binary variable is also called an indicator variable.

A dummy variable is also called a(n)

The ________ measures the total variability in Y about the mean.

The coefficients of each independent variable in a multiple regression model represent slopes.

The SST measures the total variability in the dependent variable about the regression line.

Another name for the "Multiple R" that is given in Excel is ________.

One purpose of regression is to predict the value of one variable based on the other variable.

The standard error of the estimate is also called the variance of the regression.

The errors in a regression model are assumed to have zero variance.

If every point lies on the regression line,r² = ________.

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

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

Filters

Exam 4: Regression Models

The regression line minimizes the sum of the ________.

Both the p-value for the F-test and r2 can be interpreted the same with multiple regression models as they are with simple linear models.

The adjusted r2 will always increase as additional variables are added to the model.

The coefficient of determination resulting from a particular regression analysis was 0.85.What was the correlation coefficient,assuming a positive linear relationship?

In regression,a binary variable is also called an indicator variable.

A dummy variable is also called a(n)

The ________ measures the total variability in Y about the mean.

The coefficients of each independent variable in a multiple regression model represent slopes.

The SST measures the total variability in the dependent variable about the regression line.

Another name for the "Multiple R" that is given in Excel is ________.

One purpose of regression is to predict the value of one variable based on the other variable.

The standard error of the estimate is also called the variance of the regression.

The errors in a regression model are assumed to have zero variance.

If every point lies on the regression line,r2 = ________.

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

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

Filters

Both the p-value for the F-test and r² can be interpreted the same with multiple regression models as they are with simple linear models.

The adjusted r² will always increase as additional variables are added to the model.

If every point lies on the regression line,r² = ________.

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