Question 1

A regression diagnostic tool used to study the possible effects of collinearity is

Accepted Answer

A)  the slope. 
B)  the Y-intercept. 
C)  the VIF. 
D)  the standard error of the estimate. 
A)  the slope. 
B)  the Y-intercept. 
C)  the VIF. 
D)  the standard error of the estimate.

Question 2

SCENARIO 15-1  
-Referring to Scenario 15-1, what is the value of the test statistic for testing whether there is an
Upward curvature in the response curve relating the demand (Y)and the price (X)?

Accepted Answer

A)  -5.14 
B)  0.95 
C)  373 
D)  None of the above. 
A)  -5.14 
B)  0.95 
C)  373 
D)  None of the above.

Question 3

Accepted Answer

A) True 
 B)False

Question 4

True or False: The goals of model building are to find a good model with the fewest independent
variables that is easier to interpret and has lower probability of collinearity.

Accepted Answer

A) True 
 B)False

Question 5

True or False: Collinearity is present when there is a high degree of correlation between the
dependent variable and any of the independent variables.

Accepted Answer

A) True 
 B)False

Question 6

SCENARIO 15-4   
15-16 Multiple Regression Model Building  
-

Accepted Answer

Question 7

The logarithm transformation can be used

Accepted Answer

A)  to overcome violations to the autocorrelation assumption. 
B)  to test for possible violations to the autocorrelation assumption. 
C)  to overcome violations to the homoscedasticity assumption. 
D)  to test for possible violations to the homoscedasticity assumption. 
A)  to overcome violations to the autocorrelation assumption. 
B)  to test for possible violations to the autocorrelation assumption. 
C)  to overcome violations to the homoscedasticity assumption. 
D)  to test for possible violations to the homoscedasticity assumption.

Question 8

True or False: Collinearity will result in excessively low standard errors of the parameter
estimates reported in the regression output.

Accepted Answer

A) True 
 B)False

Question 9

.

Accepted Answer

A) True 
 B)False

Question 10

Accepted Answer

Question 11

The Variance Inflationary Factor (VIF)measures the

Accepted Answer

A)  correlation of the X variables with the Y variable. 
B)  correlation of the X variables with each other. 
C)  contribution of each X variable with the Y variable after all other X variables are included in the model. 
D)  standard deviation of the slope. 
A)  correlation of the X variables with the Y variable. 
B)  correlation of the X variables with each other. 
C)  contribution of each X variable with the Y variable after all other X variables are included in the model. 
D)  standard deviation of the slope.

Question 12

Accepted Answer

Question 13

Accepted Answer

A) True 
 B)False

Question 14

SCENARIO 15-6  
-True or False: Referring to Scenario 15-6, the variable   
should be dropped to remove
collinearity?

Accepted Answer

A) True 
 B)False

Question 15

SCENARIO 15-4   
15-16 Multiple Regression Model Building  
-

Accepted Answer

Question 16

SCENARIO 15-2  
-

Accepted Answer

Question 17

True or False: In data mining where huge data sets are being explored to discover relationships
among a large number of variables, the best-subsets approach is more practical than the stepwise
regression approach.

Accepted Answer

A) True 
 B)False

Question 18

SCENARIO 15-3
A chemist employed by a pharmaceutical firm has developed a muscle relaxant.She took a sample of
14 people suffering from extreme muscle constriction.She gave each a vial containing a dose (X)of
the drug and recorded the time to relief (Y)measured in seconds for each.She fit a curvilinear model
to this data.The results obtained by Microsoft Excel follow  
-Referring to Scenario 15-3, the prediction of time to relief for a person receiving a dose of 10
units of the drug is ________.

Accepted Answer

The answer of SCENARIO 15-3
A chemist employed by a pharmaceutical...

Question 19

SCENARIO 15-6  
-True or False: Referring to Scenario 15-6, the variable   
should be dropped to remove
collinearity?

Accepted Answer

A) True 
 B)False

Question 20

SCENARIO 15-4   
15-16 Multiple Regression Model Building  
-True or False: Referring to Scenario 15-4, the residual plot suggests that a nonlinear model on %
attendance may be a better model.

Accepted Answer

A) True 
 B)False

A regression diagnostic tool used to study the possible effects of collinearity is

SCENARIO 15-1 -Referring to Scenario 15-1, what is the value of the test statistic for testing whether there is an Upward curvature in the response curve relating the demand (Y)and the price (X)?

True or False: The goals of model building are to find a good model with the fewest independent variables that is easier to interpret and has lower probability of collinearity.

True or False: Collinearity is present when there is a high degree of correlation between the dependent variable and any of the independent variables.

SCENARIO 15-4 15-16 Multiple Regression Model Building -

The logarithm transformation can be used

True or False: Collinearity will result in excessively low standard errors of the parameter estimates reported in the regression output.

.

The Variance Inflationary Factor (VIF)measures the

SCENARIO 15-6 -True or False: Referring to Scenario 15-6, the variable should be dropped to remove collinearity?

SCENARIO 15-4 15-16 Multiple Regression Model Building -

SCENARIO 15-2 -

True or False: In data mining where huge data sets are being explored to discover relationships among a large number of variables, the best-subsets approach is more practical than the stepwise regression approach.

SCENARIO 15-6 -True or False: Referring to Scenario 15-6, the variable should be dropped to remove collinearity?

SCENARIO 15-4 15-16 Multiple Regression Model Building -True or False: Referring to Scenario 15-4, the residual plot suggests that a nonlinear model on % attendance may be a better model.

Defining and Collecting Data

Organizing and Visualizing

Numerical Descriptive Measures

Basic Probability

Discrete Probability Distributions

Conthe Tinuonormausl Disdis Tributionstribution and Other

Sampling Distributions

Confidence Interval Estimation

Fundamentals of Hypothesis Testing: One-Sample Tests

Two-Sample Tests

Analysis of Variance

Chi-Square and Nonparametric

Simple Linear Regression

Introduction to Multiple

Time-Series Forecasting

Business Analytics

A Roadmap for Analyzing Data

Statistical Applications in Quality Management

Decision Making

Filters

Exam 15: Multiple Regression

A regression diagnostic tool used to study the possible effects of collinearity is

SCENARIO 15-1 -Referring to Scenario 15-1, what is the value of the test statistic for testing whether there is an Upward curvature in the response curve relating the demand (Y)and the price (X)?

True or False: The goals of model building are to find a good model with the fewest independent variables that is easier to interpret and has lower probability of collinearity.

True or False: Collinearity is present when there is a high degree of correlation between the dependent variable and any of the independent variables.

SCENARIO 15-4 15-16 Multiple Regression Model Building -

The logarithm transformation can be used

True or False: Collinearity will result in excessively low standard errors of the parameter estimates reported in the regression output.

.

The Variance Inflationary Factor (VIF)measures the

SCENARIO 15-6 -True or False: Referring to Scenario 15-6, the variable should be dropped to remove collinearity?

SCENARIO 15-4 15-16 Multiple Regression Model Building -

SCENARIO 15-2 -

True or False: In data mining where huge data sets are being explored to discover relationships among a large number of variables, the best-subsets approach is more practical than the stepwise regression approach.

SCENARIO 15-6 -True or False: Referring to Scenario 15-6, the variable should be dropped to remove collinearity?

SCENARIO 15-4 15-16 Multiple Regression Model Building -True or False: Referring to Scenario 15-4, the residual plot suggests that a nonlinear model on % attendance may be a better model.

Defining and Collecting Data

Organizing and Visualizing

Numerical Descriptive Measures

Basic Probability

Discrete Probability Distributions

Conthe Tinuonormausl Disdis Tributionstribution and Other

Sampling Distributions

Confidence Interval Estimation

Fundamentals of Hypothesis Testing: One-Sample Tests

Two-Sample Tests

Analysis of Variance

Chi-Square and Nonparametric

Simple Linear Regression

Introduction to Multiple

Time-Series Forecasting

Business Analytics

A Roadmap for Analyzing Data

Statistical Applications in Quality Management

Decision Making

Filters