Question 1

An F-test is used to determine if there is a relationship between the dependent and independent variables.

Accepted Answer

A) True 
 B)False

Question 2

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

Accepted Answer

A) True 
 B)False

Question 3

Multicollinearity exists when a variable is correlated to other variables.

Accepted Answer

A) True 
 B)False

Question 4

In regression, an independent variable is sometimes called a response variable.

Accepted Answer

A) True 
 B)False

Question 5

A dummy variable is also called a(n)

Accepted Answer

A) indicator variable. 
B) dependent variable. 
C) continuous variable. 
D) response variable. 
A) indicator variable. 
B) dependent variable. 
C) continuous variable. 
D) response variable.

Question 6

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

Accepted Answer

A) True 
 B)False

Question 7

The multiple regression model includes several dependent variables.

Accepted Answer

A) True 
 B)False

Question 8

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 + $1,2

Question 9

A prediction equation for sales and payroll was performed using simple linear regression.In the regression printout shown below, which of the following statements is not true? SUMMARY OUTPUT
  ANOVA

Accepted Answer

A) Payroll is a good predictor of Sales based on α = 0.05. 
B) There is evidence of a positive linear relationship between Sales and Payroll based on α = 0.05. 
C) Payroll is not a good predictor of Sales based on α = 0.01. 
D) The coefficient of determination is equal to 0.833333. 
A) Payroll is a good predictor of Sales based on α = 0.05. 
B) There is evidence of a positive linear relationship between Sales and Payroll based on α = 0.05. 
C) Payroll is not a good predictor of Sales based on α = 0.01. 
D) The coefficient of determination is equal to 0.833333.

Question 10

The sum of squared error (SSE)is

Accepted Answer

A) a measure of the total variation in Y about the mean. 
B) a measure of the total variation in X about the mean. 
C) a measure in the variation of Y about the regression line. 
D) a measure in the variation of X about the regression line. 
A) a measure of the total variation in Y about the mean. 
B) a measure of the total variation in X about the mean. 
C) a measure in the variation of Y about the regression line. 
D) a measure in the variation of X about the regression line.

Question 11

What can be said about a correlation coefficient of +1?

Accepted Answer

This is a perfect positive cor

Question 12

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

Accepted Answer

-(0.657)1/

Question 13

Table 4.1
SUMMARY OUTPUT
   ANOVA
    
-Consider the output shown in Table 4.1.What is the value of the regression df?

Accepted Answer

A) 0 
B) 1 
C) 2 
D) 3 
A) 0 
B) 1 
C) 2 
D) 3

Question 14

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.
SUMMARY OUTPUT
   ANOVA
     (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 15

Which of these statements is best?

Accepted Answer

A) In any regression model, there is an implicit assumption that there is no preexisting relationship between the variables. 
B) In regression, there is random error that can be predicted. 
C) Estimates of the slope, intercept, and error of a regression model are found from sample data. 
D) Error is the difference in the actual value and the predicted value. 
A) In any regression model, there is an implicit assumption that there is no preexisting relationship between the variables. 
B) In regression, there is random error that can be predicted. 
C) Estimates of the slope, intercept, and error of a regression model are found from sample data. 
D) Error is the difference in the actual value and the predicted value.

Question 16

The MBA program surveyed the catastrophe that was his fall 2017 intake.His 257 admitted students had performed miserably and he needed to determine why.He built a regression model to predict their overall class average after their first semester based on these factors that weighed heavily in their admission process: undergraduate GPA, GMAT score, years of professional employment, shoe size, TOEFL score, and 40 yard dash.What value of F is critical at the 0.05 level?

Accepted Answer

A) 2.13 
B) 0.27 
C) 0.47 
D) 3.69 
A) 2.13 
B) 0.27 
C) 0.47 
D) 3.69

Question 17

The sum of the squares total (SST)

Accepted Answer

A) measures the total variability in Y about the mean. 
B) measures the total variability in X about the mean. 
C) measures the variability in Y about the regression line. 
D) measures the variability in X about the regression line. 
A) measures the total variability in Y about the mean. 
B) measures the total variability in X about the mean. 
C) measures the variability in Y about the regression line. 
D) measures the variability in X about the regression line.

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 research has come up with the following prediction equation:
Y = $18012.24 + 1432.37X1 - 4.07 X2 where X1 = Yrs Exp and X2 = Yrs Exp2
(a)If a teacher has 7 years of experience, what is the expected salary?
(b)If teacher has 10 years of experience, what is the expected salary?

Accepted Answer

(a)$18012.24 + 1432.

Question 19

What can be said about an r2 value of 0.96?

Accepted Answer

This indicates that 96% of the

Question 20

For statistical tests of significance about the coefficients, the null hypothesis is that the slope is 1.

Accepted Answer

A) True 
 B)False

An F-test is used to determine if there is a relationship between the dependent and independent variables.

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

Multicollinearity exists when a variable is correlated to other variables.

In regression, an independent variable is sometimes called a response variable.

A dummy variable is also called a(n)

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

The multiple regression model includes several dependent variables.

A prediction equation for sales and payroll was performed using simple linear regression.In the regression printout shown below, which of the following statements is not true? SUMMARY OUTPUT ANOVA

The sum of squared error (SSE)is

What can be said about a correlation coefficient of +1?

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

Table 4.1 SUMMARY OUTPUT ANOVA -Consider the output shown in Table 4.1.What is the value of the regression df?

Which of these statements is best?

The sum of the squares total (SST)

What can be said about an r² value of 0.96?

For statistical tests of significance about the coefficients, the null hypothesis is that the slope is 1.

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

An F-test is used to determine if there is a relationship between the dependent and independent variables.

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

Multicollinearity exists when a variable is correlated to other variables.

In regression, an independent variable is sometimes called a response variable.

A dummy variable is also called a(n)

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

The multiple regression model includes several dependent variables.

A prediction equation for sales and payroll was performed using simple linear regression.In the regression printout shown below, which of the following statements is not true? SUMMARY OUTPUT ANOVA

The sum of squared error (SSE)is

What can be said about a correlation coefficient of +1?

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

Table 4.1 SUMMARY OUTPUT ANOVA -Consider the output shown in Table 4.1.What is the value of the regression df?

Which of these statements is best?

The sum of the squares total (SST)

What can be said about an r2 value of 0.96?

For statistical tests of significance about the coefficients, the null hypothesis is that the slope is 1.

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

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

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?