Question 1

Interaction exists in a multiple regression model when:

Accepted Answer

A) one independent variable affects the relationship between another independent variable and the dependent variable. 
B) multicollinearity is present in a regression model. 
C) the regression model is overall insignificant. 
D) a polynomial model used. 
A) one independent variable affects the relationship between another independent variable and the dependent variable. 
B) multicollinearity is present in a regression model. 
C) the regression model is overall insignificant. 
D) a polynomial model used.

Question 2

Models can be specified as linear or nonlinear.

Accepted Answer

A) True 
 B)False

Question 3

A decision maker is considering including two additional variables into a regression model that has as the dependent variable,Total Sales.The first additional variable is the region of the country (North,South,East,or West)in which the company is located.The second variable is the type of business (Manufacturing,Financial,Information Services,or Other).Given this,how many additional variables will be incorporated into the model?

Accepted Answer

A) 2 
B) 6 
C) 8 
D) 9 
A) 2 
B) 6 
C) 8 
D) 9

Question 4

Residuals are calculated by e = y -   .

Accepted Answer

A) True 
 B)False

Question 5

In a second-order polynomial regression model,the regression coefficient,B2,will be positive if the parabola opens downward and negative when the parabola opens upward.

Accepted Answer

A) True 
 B)False

Question 6

Consider the following regression equation:   = 356 + 180x1 - 2.5x2.The x1 variable is a quantitative variable and the x2 variable is a dummy with values 1 and 0.Given this,we can interpret the slope coefficient on variable x2 as follows: Holding x1 constant,if the value of x2 is changed from 0 to 1,the average value of y will decrease by 2.5 units.

Accepted Answer

A) True 
 B)False

Question 7

The forward selection method and the backward elimination method will always lead to choosing the same final regression model.

Accepted Answer

A) True 
 B)False

Question 8

A decision maker is considering constructing a multiple regression model with two independent variables.The correlation between x1 and y is 0.70,and the correlation between variable x2 and y is 0.50.Based on this,the regression model containing both independent variables will explain 74 percent of the variation in the dependent variable.

Accepted Answer

A) True 
 B)False

Question 9

Based on the correlations below:
   we could say that x1 accounts for 64 percent of the variation in y and x2 accounts for 49 percent of the variation in y.So if both xs are included in a multiple regression model,then the resulting R-square = 1.13.

Accepted Answer

A) True 
 B)False

Question 10

A major car magazine has recently collected data on 30 leading cars in the U.S.market.It is interested in building a multiple regression model to explain the variation in highway miles.The following correlation matrix has been computed from the data collected:
   If only one independent variable (ignoring city mileage)is to be used in explaining the dependent variable in a regression model,the percentage of variation that will be explained will be nearly 74 percent.

Accepted Answer

A) True 
 B)False

Question 11

A major car magazine has recently collected data on 30 leading cars in the U.S.market.It is interested in building a multiple regression model to explain the variation in highway miles.The following correlation matrix has been computed from the data collected:
   If the independent variables,curb weight,cylinders,and horsepower are used together in a multiple regression model,there may be a potential problem with multicollinearity since horsepower and cylinders are highly correlated.

Accepted Answer

A) True 
 B)False

Question 12

Which of the following is the difference between forward selection and standard stepwise regression?

Accepted Answer

A) In the standard stepwise regression,variables that were added at earlier steps can be removed at later steps,which is not the case with forward selection. 
B) The standard stepwise approach will generally produce a regression model with a higher R-square value than the forward selection approach. 
C) Forward selection begins by selecting the variable with the highest correlation with the dependent variable and then proceeds to select subsequent variables in order of their F-to-enter value,while standard stepwise selects the variables in the order specified by the decision maker and then removes them from the model as needed. 
D) There are no appreciable differences between the two methods,just different names for the same technique. 
A) In the standard stepwise regression,variables that were added at earlier steps can be removed at later steps,which is not the case with forward selection. 
B) The standard stepwise approach will generally produce a regression model with a higher R-square value than the forward selection approach. 
C) Forward selection begins by selecting the variable with the highest correlation with the dependent variable and then proceeds to select subsequent variables in order of their F-to-enter value,while standard stepwise selects the variables in the order specified by the decision maker and then removes them from the model as needed. 
D) There are no appreciable differences between the two methods,just different names for the same technique.

Question 13

A major car magazine has recently collected data on 30 leading cars in the U.S.market.It is interested in building a multiple regression model to explain the variation in highway miles.The following correlation matrix has been computed from the data collected:
   The analysts also produced the following multiple regression output using curb weight,cylinders,and horsepower as the three independent variables.Note,a number of the output fields are missing,but can be determined from the information provided.   Based on the information provided,using a 0.05 level of statistical significance,both curb weight and horsepower are statistically significant variables in explaining the variation in the dependent variable when they are included in the model along with cylinders.

Accepted Answer

A) True 
 B)False

Question 14

The variance inflation factor (VIF)provides a measure for each independent variable of how much multicollinearity is associated with that particular independent variable.

Accepted Answer

A) True 
 B)False

Question 15

The variance inflation factor is an indication of how much multicollinearity there is in the regression model.

Accepted Answer

A) True 
 B)False

Question 16

Standard stepwise regression combines attributes of both forward selection and backward elimination.

Accepted Answer

A) True 
 B)False

Question 17

In multiple regression analysis,the residual is the absolute difference between the actual value of y and the predicted value of y.

Accepted Answer

A) True 
 B)False

Question 18

A multiple regression is shown below for a data set of yachts where the dependent variable is the price of the boat in thousands of dollars.   Given this information,what percentage of variation in the dependent variable is explained by the regression model?

Accepted Answer

A) Approximately 68 percent 
B) About 83 percent 
C) About 37 percent 
D) About 60 percent 
A) Approximately 68 percent 
B) About 83 percent 
C) About 37 percent 
D) About 60 percent

Question 19

One of the variables that are being considered for inclusion in a multiple regression model is marital status of the customer.There are four possible responses listed for this variable.Based on this,four dummy variables will need to be created and incorporated into the regression model.

Accepted Answer

A) True 
 B)False

Question 20

A major car magazine has recently collected data on 30 leading cars in the U.S.market.It is interested in building a multiple regression model to explain the variation in highway miles.The following correlation matrix has been computed from the data collected:
   The analysts also produced the following multiple regression output using curb weight,cylinders,and horsepower as the three independent variables.Note,a number of the output fields are missing,but can be determined from the information provided.   If the analysts are interested in testing whether the overall regression model is statistically significant,the appropriate null and alternative hypotheses are:
H0 : β1 = β2 = β3
Ha : β1 ≠ β2 ≠ β3

Accepted Answer

A) True 
 B)False

Interaction exists in a multiple regression model when:

Models can be specified as linear or nonlinear.

Residuals are calculated by e = y - .

In a second-order polynomial regression model,the regression coefficient,B₂,will be positive if the parabola opens downward and negative when the parabola opens upward.

The forward selection method and the backward elimination method will always lead to choosing the same final regression model.

Based on the correlations below: we could say that x₁ accounts for 64 percent of the variation in y and x₂ accounts for 49 percent of the variation in y.So if both xs are included in a multiple regression model,then the resulting R-square = 1.13.

Which of the following is the difference between forward selection and standard stepwise regression?

The variance inflation factor (VIF)provides a measure for each independent variable of how much multicollinearity is associated with that particular independent variable.

The variance inflation factor is an indication of how much multicollinearity there is in the regression model.

Standard stepwise regression combines attributes of both forward selection and backward elimination.

In multiple regression analysis,the residual is the absolute difference between the actual value of y and the predicted value of y.

A multiple regression is shown below for a data set of yachts where the dependent variable is the price of the boat in thousands of dollars. Given this information,what percentage of variation in the dependent variable is explained by the regression model?

One of the variables that are being considered for inclusion in a multiple regression model is marital status of the customer.There are four possible responses listed for this variable.Based on this,four dummy variables will need to be created and incorporated into the regression model.

The Where,Why,and How of Data Collection

Graphs,Charts and Tablesdescribing Your Data

Describing Data Using Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Introduction to Continuous Probability Distributions

Introduction to Sampling Distributions

Estimating Single Population Parameters

Introduction to Hypothesis Testing

Estimation and Hypothesis Testing for Two Population Parameters

Hypothesis Tests and Estimation for Population Variances

Analysis of Variance

Goodness-Of-Fit Tests and Contingency Analysis

Introduction to Linear Regression and Correlation Analysis

Analyzing and Forecasting Time-Series Data

Introduction to Nonparametric Statistics

Introduction to Quality and Statistical Process Control

Filters

Exam 15: Multiple Regression Analysis and Model Building

Interaction exists in a multiple regression model when:

Models can be specified as linear or nonlinear.

Residuals are calculated by e = y - .

In a second-order polynomial regression model,the regression coefficient,B2,will be positive if the parabola opens downward and negative when the parabola opens upward.

The forward selection method and the backward elimination method will always lead to choosing the same final regression model.

Based on the correlations below: we could say that x1 accounts for 64 percent of the variation in y and x2 accounts for 49 percent of the variation in y.So if both xs are included in a multiple regression model,then the resulting R-square = 1.13.

Which of the following is the difference between forward selection and standard stepwise regression?

The variance inflation factor (VIF)provides a measure for each independent variable of how much multicollinearity is associated with that particular independent variable.

The variance inflation factor is an indication of how much multicollinearity there is in the regression model.

Standard stepwise regression combines attributes of both forward selection and backward elimination.

In multiple regression analysis,the residual is the absolute difference between the actual value of y and the predicted value of y.

A multiple regression is shown below for a data set of yachts where the dependent variable is the price of the boat in thousands of dollars. Given this information,what percentage of variation in the dependent variable is explained by the regression model?

One of the variables that are being considered for inclusion in a multiple regression model is marital status of the customer.There are four possible responses listed for this variable.Based on this,four dummy variables will need to be created and incorporated into the regression model.

The Where,Why,and How of Data Collection

Graphs,Charts and Tablesdescribing Your Data

Describing Data Using Numerical Measures

Introduction to Probability

Discrete Probability Distributions

Introduction to Continuous Probability Distributions

Introduction to Sampling Distributions

Estimating Single Population Parameters

Introduction to Hypothesis Testing

Estimation and Hypothesis Testing for Two Population Parameters

Hypothesis Tests and Estimation for Population Variances

Analysis of Variance

Goodness-Of-Fit Tests and Contingency Analysis

Introduction to Linear Regression and Correlation Analysis

Analyzing and Forecasting Time-Series Data

Introduction to Nonparametric Statistics

Introduction to Quality and Statistical Process Control

Filters

In a second-order polynomial regression model,the regression coefficient,B₂,will be positive if the parabola opens downward and negative when the parabola opens upward.

Based on the correlations below: we could say that x₁ accounts for 64 percent of the variation in y and x₂ accounts for 49 percent of the variation in y.So if both xs are included in a multiple regression model,then the resulting R-square = 1.13.