Question 1

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 C

Question 2

The mean square error (MSE) is

Accepted Answer

A)  denoted by s. 
B)  denoted by k. 
C)  the SSE divided by the number of observations. 
D)  the SSE divided by the degrees of freedom. 
E)  None of the above 
A)  denoted by s. 
B)  denoted by k. 
C)  the SSE divided by the number of observations. 
D)  the SSE divided by the degrees of freedom. 
E)  None of the above D

Question 3

Explain the purposes of regression models.

Accepted Answer

to understand the relationship between variables and to predict the value of one variable using the value of another variable

Question 4

The multiple regression model includes several dependent variables.

Accepted Answer

A) True 
 B)False

Question 5

A large school district is reevaluating its teachers' salaries. They have decided to use regression analysis to predict mean teachers' salaries at each elementary school. The researcher uses years of experience to predict salary. The resulting equation was:
Y = 23,313.22 + 1,210.89X, where Y = salary and X = years of experience
(a) If a teacher has 10 years of experience, what is the forecasted salary?
(b) If a teacher has 5 years of experience, what is the forecasted salary?
(c) Based on this equation, for every additional year of service, a teacher could expect his or her salary to increase by how much?

Accepted Answer

(a) $23,313.22 + $1,210.89(10)

Question 6

Estimates of the slope, intercept, and error of a regression model are found from sample data.

Accepted Answer

A) True 
 B)False

Question 7

The condition of an independent variable being correlated to one or more other independent variables is referred to as

Accepted Answer

A)  multicollinearity. 
B)  statistical significance. 
C)  linearity. 
D)  nonlinearity. 
E)  The significance level for the F-test is not valid. 
A)  multicollinearity. 
B)  statistical significance. 
C)  linearity. 
D)  nonlinearity. 
E)  The significance level for the F-test is not valid.

Question 8

To include qualitative data in regression analysis, you must first create a ________ variable.

Accepted Answer

dummy or b

Question 9

A healthcare executive is using regression to predict total revenues. She has decided to include both patient length of stay and insurance type in her model. Insurance type can be grouped into three categories: Government-Funded, Private-Pay, and Other. Her model is

Accepted Answer

A)  Y = b0. 
B)  Y = b0 + b1 X1. 
C)  Y = b0 + b1 X1 + b2 X2. 
D)  Y = b0 + b1 X1 + b2 X2 + b3 X3. 
E)  Y = b0 + b1 X1 + b2 X2 + b3 X3 + b4 X4. 
A)  Y = b0. 
B)  Y = b0 + b1 X1. 
C)  Y = b0 + b1 X1 + b2 X2. 
D)  Y = b0 + b1 X1 + b2 X2 + b3 X3. 
E)  Y = b0 + b1 X1 + b2 X2 + b3 X3 + b4 X4.

Question 10

Suppose that you believe that a cubic relationship exists between the independent variable (of time) and the dependent variable Y. Which of the following would represent a valid linear regression model?

Accepted Answer

A)  Y = b0 + b1 X, where X = time3 
B)  Y = b0 + b1 X3, where X = time 
C)  Y = b0 + 3b1 X, where X = time3 
D)  Y = b0 + 3b1 X, where X = time 
E)  Y = b0 + b1 X, where X = time1/3 
A)  Y = b0 + b1 X, where X = time3 
B)  Y = b0 + b1 X3, where X = time 
C)  Y = b0 + 3b1 X, where X = time3 
D)  Y = b0 + 3b1 X, where X = time 
E)  Y = b0 + b1 X, where X = time1/3

Question 11

Describe the purpose and structure of a scatter diagram.

Accepted Answer

A scatter diagram is a graphical method

Question 12

An air conditioning and heating repair firm conducted a study to determine if the average outside temperature, thickness of the insulation, and age of the heating equipment could be used to predict the electric bill for a home during the winter months in Houston, Texas. The resulting regression equation was:
Y = 256.89 - 1.45X1 - 11.26X2 + 6.10X3, where Y = monthly cost, X1 = average temperature, X2 = insulation thickness, and X3 = age of heating equipment
(a) If December has an average temperature of 45 degrees and the heater is 2 years old with insulation that is 6 inches thick, what is the forecasted monthly electric bill?
(b) If January has an average temperature of 40 degrees and the heating equipment is 12 years old with insulation that is 2 inches thick, what is the forecasted monthly electric bill?

Accepted Answer

(a) $256.89 - 1.45(45) - 11.26

Question 13

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 14

The dependent variable is also called the response variable.

Accepted Answer

A) True 
 B)False

Question 15

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

Accepted Answer

A) True 
 B)False

Question 16

A large school district is reevaluating its teachers' salaries. They have decided to use regression analysis to predict mean teacher salaries at each elementary school. The researcher would like to examine the significance of a following quadratic model for predicting salary based on years of experience.
Y = β0 + β1X1 + β2X2 + ε where X1 = Yrs Exp and X2 = Yrs Exp2   (a) What is the adjusted r2?
(b) What is the prediction equation?

Accepted Answer

(a) 0.855

Question 17

Which of the following statements is false concerning the hypothesis testing procedure for a regression model?

Accepted Answer

A)  The F-test statistic is used. 
B)  The null hypothesis is that the true slope coefficient is equal to zero. 
C)  The null hypothesis is rejected if the adjusted r2 is above the critical value. 
D)  An α level must be selected. 
E)  The alternative hypothesis is that the true slope coefficient is not equal to zero. 
A)  The F-test statistic is used. 
B)  The null hypothesis is that the true slope coefficient is equal to zero. 
C)  The null hypothesis is rejected if the adjusted r2 is above the critical value. 
D)  An α level must be selected. 
E)  The alternative hypothesis is that the true slope coefficient is not equal to zero.

Question 18

A large school district is reevaluating its teachers' salaries. They have decided to use regression analysis to predict mean teacher salaries at each elementary school. The researcher uses years of experience to predict salary. The raw data is given in the table below. The resulting equation was:
Y = 19389.21 + 1330.12X, where Y = salary and X = years of experience   (a) Develop a scatter diagram.
(b) What is the correlation coefficient?
(c) What is the coefficient of determination?

Accepted Answer

(a) @#IMG-DLM& (b) .

Question 19

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) Y

Question 20

A high correlation always implies that one variable is causing a change in the other variable.

Accepted Answer

A) True 
 B)False

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

The mean square error (MSE) is

Explain the purposes of regression models.

The multiple regression model includes several dependent variables.

Estimates of the slope, intercept, and error of a regression model are found from sample data.

The condition of an independent variable being correlated to one or more other independent variables is referred to as

To include qualitative data in regression analysis, you must first create a ________ variable.

A healthcare executive is using regression to predict total revenues. She has decided to include both patient length of stay and insurance type in her model. Insurance type can be grouped into three categories: Government-Funded, Private-Pay, and Other. Her model is

Suppose that you believe that a cubic relationship exists between the independent variable (of time) and the dependent variable Y. Which of the following would represent a valid linear regression model?

Describe the purpose and structure of a scatter diagram.

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

The dependent variable is also called the response variable.

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

Which of the following statements is false concerning the hypothesis testing procedure for a regression model?

A high correlation always implies that one variable is causing a change in the other variable.

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

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Exam 4: Regression Models

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

The mean square error (MSE) is

Explain the purposes of regression models.

The multiple regression model includes several dependent variables.

Estimates of the slope, intercept, and error of a regression model are found from sample data.

The condition of an independent variable being correlated to one or more other independent variables is referred to as

To include qualitative data in regression analysis, you must first create a ________ variable.

A healthcare executive is using regression to predict total revenues. She has decided to include both patient length of stay and insurance type in her model. Insurance type can be grouped into three categories: Government-Funded, Private-Pay, and Other. Her model is

Suppose that you believe that a cubic relationship exists between the independent variable (of time) and the dependent variable Y. Which of the following would represent a valid linear regression model?

Describe the purpose and structure of a scatter diagram.

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

The dependent variable is also called the response variable.

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

Which of the following statements is false concerning the hypothesis testing procedure for a regression model?

A high correlation always implies that one variable is causing a change in the other variable.

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