Question 1

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. 
E)  None of the above 
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. 
E)  None of the above

Question 2

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 3

Which of the following is not a common pitfall of regression?

Accepted Answer

A)  If the assumptions are not met, the statistical tests may not be valid. 
B)  Nonlinear relationships cannot be incorporated. 
C)  Two variables may be highly correlated to one another but one is not causing the other to change. 
D)  Concluding that a statistically significant relationship implies practical value. 
E)  Using a regression equation beyond the range of X is very questionable. 
A)  If the assumptions are not met, the statistical tests may not be valid. 
B)  Nonlinear relationships cannot be incorporated. 
C)  Two variables may be highly correlated to one another but one is not causing the other to change. 
D)  Concluding that a statistically significant relationship implies practical value. 
E)  Using a regression equation beyond the range of X is very questionable.

Question 4

The best model is a statistically significant model with a high r-square and few variables.

Accepted Answer

A) True 
 B)False

Question 5

The diagram below illustrates data with a

Accepted Answer

A)  negative correlation coefficient. 
B)  zero correlation coefficient. 
C)  positive correlation coefficient. 
D)  correlation coefficient equal to +1. 
E)  None of the above 
A)  negative correlation coefficient. 
B)  zero correlation coefficient. 
C)  positive correlation coefficient. 
D)  correlation coefficient equal to +1. 
E)  None of the above

Question 6

Which of the following statements (are) is not true about regression models?

Accepted Answer

A)  Estimates of the slope are found from sample data. 
B)  The regression line minimizes the sum of the squared errors. 
C)  The error is found by subtracting the actual data value from the predicted data value. 
D)  The dependent variable is the explanatory variable. 
E)  The intercept coefficient is not typically interpreted. 
A)  Estimates of the slope are found from sample data. 
B)  The regression line minimizes the sum of the squared errors. 
C)  The error is found by subtracting the actual data value from the predicted data value. 
D)  The dependent variable is the explanatory variable. 
E)  The intercept coefficient is not typically interpreted.

Question 7

One purpose of regression is to understand the relationship between variables.

Accepted Answer

A) True 
 B)False

Question 8

Which of the following equalities is correct?

Accepted Answer

A)  SST = SSR + SSE 
B)  SSR = SST + SSE 
C)  SSE = SSR + SST 
D)  SST = SSC + SSR 
E)  SSE = Actual Value - Predicted Value 
A)  SST = SSR + SSE 
B)  SSR = SST + SSE 
C)  SSE = SSR + SST 
D)  SST = SSC + SSR 
E)  SSE = Actual Value - Predicted Value

Question 9

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

Accepted Answer

A) True 
 B)False

Question 10

Explain what r2 is.

Accepted Answer

It is a value between 0 and +1

Question 11

The variable to be predicted is the dependent variable.

Accepted Answer

A) True 
 B)False

Question 12

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

Accepted Answer

A) True 
 B)False

Question 13

The regression model assumes the error terms are dependent.

Accepted Answer

A) True 
 B)False

Question 14

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

Accepted Answer

A) True 
 B)False

Question 15

Often, a plot of the residuals will highlight any glaring violations of the assumptions.

Accepted Answer

A) True 
 B)False

Question 16

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

Accepted Answer

Question 17

The regression model assumes the errors are normally distributed.

Accepted Answer

A) True 
 B)False

Question 18

An automated process to systematically add or delete independent variables from a regression model is known as

Accepted Answer

A)  nonlinear transformations. 
B)  multicollinearity. 
C)  multiple regression. 
D)  least squares method. 
E)  None of the above 
A)  nonlinear transformations. 
B)  multicollinearity. 
C)  multiple regression. 
D)  least squares method. 
E)  None of the above

Question 19

As more variables are added to the model, what happens to the r2 value?

Accepted Answer

It usually

Question 20

If multicollinearity exists, then individual interpretation of the variables is questionable, but the overall model is still good for prediction purposes.

Accepted Answer

A) True 
 B)False

The sum of squared error (SSE) is

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

Which of the following is not a common pitfall of regression?

The best model is a statistically significant model with a high r-square and few variables.

The diagram below illustrates data with a

Which of the following statements (are) is not true about regression models?

One purpose of regression is to understand the relationship between variables.

Which of the following equalities is correct?

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

Explain what r² is.

The variable to be predicted is the dependent variable.

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

The regression model assumes the error terms are dependent.

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

Often, a plot of the residuals will highlight any glaring violations of the assumptions.

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

The regression model assumes the errors are normally distributed.

An automated process to systematically add or delete independent variables from a regression model is known as

As more variables are added to the model, what happens to the r² value?

If multicollinearity exists, then individual interpretation of the variables is questionable, but the overall model is still good for prediction purposes.

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

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Exam 4: Regression Models

The sum of squared error (SSE) is

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

Which of the following is not a common pitfall of regression?

The best model is a statistically significant model with a high r-square and few variables.

The diagram below illustrates data with a

Which of the following statements (are) is not true about regression models?

One purpose of regression is to understand the relationship between variables.

Which of the following equalities is correct?

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

Explain what r2 is.

The variable to be predicted is the dependent variable.

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

The regression model assumes the error terms are dependent.

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

Often, a plot of the residuals will highlight any glaring violations of the assumptions.

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

The regression model assumes the errors are normally distributed.

An automated process to systematically add or delete independent variables from a regression model is known as

As more variables are added to the model, what happens to the r2 value?

If multicollinearity exists, then individual interpretation of the variables is questionable, but the overall model is still good for prediction purposes.

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

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

Explain what r² is.

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

As more variables are added to the model, what happens to the r² value?