Question 1

In curvilinear regression modeling,a composite model is one that contains either the basic terms or the interactive terms but not both.

Accepted Answer

A) True 
 B)False

Question 2

In a multiple regression model,the regression coefficients are calculated such that the quantity,   ,is minimized.

Accepted Answer

A) True 
 B)False

Question 3

The following regression output is the result of a multiple regression application in which we are interested in explaining the variation in retail price of personal computers based on three independent variables,CPU speed,RAM,and hard drive capacity.However,some of the regression output has been omitted.   Given this information and your knowledge of multiple regression,what is the value for the standard error of the estimate?

Accepted Answer

The standard error of the estimate is a

Question 4

When an independent variable,that has a positive correlation with the dependent variable,receives a negative slope in a multiple regression,this is probably caused by multicollinearity.

Accepted Answer

A) True 
 B)False

Question 5

A study has recently been conducted by a major computer magazine publisher in which the objective was to develop a multiple regression model to explain the variation in price of personal computers.Three quantitative independent variables were used along with one qualitative variable.The qualitative variable was coded 1 if the computer included a monitor,0 otherwise.The following computer printout shows the final output.   Based on this information,it is possible to determine that 4 of the PCs in the data set did not have a monitor included.

Accepted Answer

A) True 
 B)False

Question 6

Assume that a time-series plot takes the form of that shown in the following graph:   Given this plot,which of the following models would likely give the best fit?

Accepted Answer

A)   
= b0b1 + b1t 
B)   
= b0 + b1t + b1t2 + b1t3 
C)   
= b0 + b1t + b1t2 
D)    
A)   
= b0b1 + b1t 
B)   
= b0 + b1t + b1t2 + b1t3 
C)   
= b0 + b1t + b1t2 
D)

Question 7

Based on the residual plot below,which of the following is correct?   The above residual plot shows:

Accepted Answer

A) linearity and nonconstant variance. 
B) nonlinearity and constant variance. 
C) linearity and constant variance. 
D) nonlinearity and nonconstant variance. 
A) linearity and nonconstant variance. 
B) nonlinearity and constant variance. 
C) linearity and constant variance. 
D) nonlinearity and nonconstant variance.

Question 8

The editors of a national automotive magazine recently studied 30 different automobiles sold in the United States with the intent of seeing whether they could develop a multiple regression model to explain the variation in highway mileage per gallon.A number of different independent variables were collected.The following correlation matrix was developed:   If only one variable were to be brought into the model,which variable should it be if the goal is to explain the highest possible percentage of variation in the dependent variable?

Accepted Answer

A) 0 to 60 mph 
B) Horsepower 
C) Curb weight 
D) Displacement 
A) 0 to 60 mph 
B) Horsepower 
C) Curb weight 
D) Displacement

Question 9

In a multiple regression model,R-square can be computed by squaring the highest correlation coefficient between the dependent variable and any independent variable.

Accepted Answer

A) True 
 B)False

Question 10

The best subsets method will involve trying fewer different regression models than stepwise regression.

Accepted Answer

A) True 
 B)False

Question 11

In a multiple regression model,it is assumed that the errors or residuals are normally distributed.

Accepted Answer

A) True 
 B)False

Question 12

A study has recently been conducted by a major computer magazine publisher in which the objective was to develop a multiple regression model to explain the variation in price of personal computers.Three quantitative independent variables were used along with one qualitative variable.The qualitative variable was coded 1 if the computer included a monitor,0 otherwise.The following computer printout shows the final output.   Based on this information,given the other variables in the model,whether or not a monitor is included has a significant impact on the price of the personal computer.

Accepted Answer

A) True 
 B)False

Question 13

The following multiple regression output was generated from a study in which two independent variables are included.The first independent variable (X1)is a quantitative variable measured on a continuous scale.The second variable (X2)is qualitative coded 0 if Yes,1 if No.   Based on this information,which of the following statements is true?

Accepted Answer

A) The model explains nearly 63 percent of the variation in the dependent variable 
B) If tested at the 0.05 significance level,the overall model would be considered statistically significant. 
C) The variable X1 has a slope coefficient that is significantly different from zero if tested at the 0.05 level of significance. 
D) All of the above are true. 
A) The model explains nearly 63 percent of the variation in the dependent variable 
B) If tested at the 0.05 significance level,the overall model would be considered statistically significant. 
C) The variable X1 has a slope coefficient that is significantly different from zero if tested at the 0.05 level of significance. 
D) All of the above are true.

Question 14

A multiple regression model of the form   = B0 + B1x + B2x2 + ε is called a second-degree polynomial model.

Accepted Answer

A) True 
 B)False

Question 15

The editors of a national automotive magazine recently studied 30 different automobiles sold in the United States with the intent of seeing whether they could develop a multiple regression model to explain the variation in highway miles per gallon.A number of different independent variables were collected.The following regression output (with some values missing)was recently presented to the editors by the magazine's analysts:   Based on this output and your understanding of multiple regression analysis,what is the value of the standard error of the estimate for this model?

Accepted Answer

A) Approximately 2.02 
B) About 5.97 
C) Approximately 14.05 
D) Nearly 8.0 
A) Approximately 2.02 
B) About 5.97 
C) Approximately 14.05 
D) Nearly 8.0

Question 16

In a multiple regression model,each regression slope coefficient measures the average change in the dependent variable for a one-unit change in the independent variable,all other variables held constant.

Accepted Answer

A) True 
 B)False

Question 17

In a multiple regression analysis with three independent variables the null hypothesis for conducting the test of the overall model is:
H0 : β0 = β1 = β2 = β3 = 0.

Accepted Answer

A) True 
 B)False

Question 18

Which of the following is an advantage of using stepwise regression compared to just entering all the independent variables at one time?

Accepted Answer

A) Stepwise will generally produce a model with a larger R-square value. 
B) The standard error of the estimate for a model constructed with stepwise regression will be larger than the one generated when all variables are entered at the same time. 
C) The stepwise regression allows the decision maker to observe the effects of multicollinearity more easily than when all the variables are entered at one time. 
D) There are no advantages of using stepwise regression over entering all variables at one time. 
A) Stepwise will generally produce a model with a larger R-square value. 
B) The standard error of the estimate for a model constructed with stepwise regression will be larger than the one generated when all variables are entered at the same time. 
C) The stepwise regression allows the decision maker to observe the effects of multicollinearity more easily than when all the variables are entered at one time. 
D) There are no advantages of using stepwise regression over entering all variables at one time.

Question 19

The editors of a national automotive magazine recently studied 30 different automobiles sold in the United States with the intent of seeing whether they could develop a multiple regression model to explain the variation in highway miles per gallon.A number of different independent variables were collected.The following regression output (with some values missing)was recently presented to the editors by the magazine's analysts:   Based on this output and your understanding of multiple regression analysis,how many degrees of freedom are associated with the Residual in the ANOVA table?

Accepted Answer

A) 19 
B) 22 
C) 7 
D) 29 
A) 19 
B) 22 
C) 7 
D) 29

Question 20

In regression model: y = β0 + β1x1 + β2
 
   + ε ,if β2 < 0,then the value of y is expected to increase with x until x reaches a certain point after which the value of y is expected to decrease.

Accepted Answer

A) True 
 B)False

In curvilinear regression modeling,a composite model is one that contains either the basic terms or the interactive terms but not both.

In a multiple regression model,the regression coefficients are calculated such that the quantity, ,is minimized.

When an independent variable,that has a positive correlation with the dependent variable,receives a negative slope in a multiple regression,this is probably caused by multicollinearity.

Assume that a time-series plot takes the form of that shown in the following graph: Given this plot,which of the following models would likely give the best fit?

Based on the residual plot below,which of the following is correct? The above residual plot shows:

In a multiple regression model,R-square can be computed by squaring the highest correlation coefficient between the dependent variable and any independent variable.

The best subsets method will involve trying fewer different regression models than stepwise regression.

In a multiple regression model,it is assumed that the errors or residuals are normally distributed.

A multiple regression model of the form = B₀ + B₁x + B₂x² + ε is called a second-degree polynomial model.

In a multiple regression model,each regression slope coefficient measures the average change in the dependent variable for a one-unit change in the independent variable,all other variables held constant.

In a multiple regression analysis with three independent variables the null hypothesis for conducting the test of the overall model is: H₀ : β₀ = β₁ = β₂ = β₃ = 0.

Which of the following is an advantage of using stepwise regression compared to just entering all the independent variables at one time?

In regression model: y = β₀ + β₁x₁ + β₂ + ε ,if β₂ < 0,then the value of y is expected to increase with x until x reaches a certain point after which the value of y is expected to decrease.

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

In curvilinear regression modeling,a composite model is one that contains either the basic terms or the interactive terms but not both.

In a multiple regression model,the regression coefficients are calculated such that the quantity, ,is minimized.

When an independent variable,that has a positive correlation with the dependent variable,receives a negative slope in a multiple regression,this is probably caused by multicollinearity.

Assume that a time-series plot takes the form of that shown in the following graph: Given this plot,which of the following models would likely give the best fit?

Based on the residual plot below,which of the following is correct? The above residual plot shows:

In a multiple regression model,R-square can be computed by squaring the highest correlation coefficient between the dependent variable and any independent variable.

The best subsets method will involve trying fewer different regression models than stepwise regression.

In a multiple regression model,it is assumed that the errors or residuals are normally distributed.

A multiple regression model of the form = B0 + B1x + B2x2 + ε is called a second-degree polynomial model.

In a multiple regression model,each regression slope coefficient measures the average change in the dependent variable for a one-unit change in the independent variable,all other variables held constant.

In a multiple regression analysis with three independent variables the null hypothesis for conducting the test of the overall model is: H0 : β0 = β1 = β2 = β3 = 0.

Which of the following is an advantage of using stepwise regression compared to just entering all the independent variables at one time?

In regression model: y = β0 + β1x1 + β2 + ε ,if β2 < 0,then the value of y is expected to increase with x until x reaches a certain point after which the value of y is expected to decrease.

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

A multiple regression model of the form = B₀ + B₁x + B₂x² + ε is called a second-degree polynomial model.

In a multiple regression analysis with three independent variables the null hypothesis for conducting the test of the overall model is: H₀ : β₀ = β₁ = β₂ = β₃ = 0.

In regression model: y = β₀ + β₁x₁ + β₂ + ε ,if β₂ < 0,then the value of y is expected to increase with x until x reaches a certain point after which the value of y is expected to decrease.