Question 1

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. 
A) multicollinearity. 
B) statistical significance. 
C) linearity. 
D) nonlinearity.

Question 2

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 3

Suppose that you believe that a quadratic 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 = time4 
B) Y = b0 + b1 X4, where X = time 
C) Y = b0 + b1 X, where X = time2 
D) Y = b0 + b1 X2, where X = time 
A) Y = b0 + b1 X, where X = time4 
B) Y = b0 + b1 X4, where X = time 
C) Y = b0 + b1 X, where X = time2 
D) Y = b0 + b1 X2, where X = time

Question 4

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

Accepted Answer

A) True 
 B)False

Question 5

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

Accepted Answer

A) True 
 B)False

Question 6

Explain what the correlation coefficient is.

Accepted Answer

It is a value between -1 and +

Question 7

The coefficient of determination gives the proportion of the variability in the dependent variable that is explained by the regression equation.

Accepted Answer

A) True 
 B)False

Question 8

Which of these statements is best?

Accepted Answer

A) In regression, an independent variable is sometimes called a response variable. 
B) One purpose of regression is to understand the relationship between variables. 
C) One purpose of regression is to predict the value of one variable based on the standard deviation of that variable. 
D) The variable to be predicted is the independent variable. 
A) In regression, an independent variable is sometimes called a response variable. 
B) One purpose of regression is to understand the relationship between variables. 
C) One purpose of regression is to predict the value of one variable based on the standard deviation of that variable. 
D) The variable to be predicted is the independent variable.

Question 9

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. 
A) 0.5 
B) -0.5 
C) 0.922 
D) There is insufficient information to answer the question.

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

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

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

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

Explain what the correlation coefficient is.

The coefficient of determination gives the proportion of the variability in the dependent variable that is explained by the regression equation.

Which of these statements is best?

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

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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Exam 4: Regression Models

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

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

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

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

Explain what the correlation coefficient is.

The coefficient of determination gives the proportion of the variability in the dependent variable that is explained by the regression equation.

Which of these statements is best?

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

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