Question 1

A standardized residual is:

Accepted Answer

A) equal to the sum of the residuals divided by n-1. 
B) the ratio of each residual divided by an estimate for the standard deviation of the residuals. 
C) a value that is normally distributed with a mean equal to zero and a standard deviation equal to one. 
D) None of the above. 
A) equal to the sum of the residuals divided by n-1. 
B) the ratio of each residual divided by an estimate for the standard deviation of the residuals. 
C) a value that is normally distributed with a mean equal to zero and a standard deviation equal to one. 
D) None of the above.

Question 2

When the best subsets approach is used in a regression application,one method for determining which of the many possible models to select for potential use is called the Cp statistic.

Accepted Answer

A) True 
 B)False

Question 3

Consider the following regression model:   = B0 + B1x1 +   + ε.If B2 > 0,then the parabola will open downward and if B2 < 0,then the parabola will open downward.

Accepted Answer

A) True 
 B)False

Question 4

A multiple regression is shown for a data set of yachts where the dependent variable is the price in thousands of dollars.   Given this information,what is the null hypothesis for testing the overall model?

Accepted Answer

A) Ho : β0 = β1 = β2 = β3 = β4 = 0 
B) Ho : β1 = β2 = β3 = β4 = 0 
C) Ho : β1 = 0 
D) Ho : β0 = 0 
A) Ho : β0 = β1 = β2 = β3 = β4 = 0 
B) Ho : β1 = β2 = β3 = β4 = 0 
C) Ho : β1 = 0 
D) Ho : β0 = 0

Question 5

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 6

When a regression equation includes a term such as x1x2 where two independent variables are multiplied,this is an interaction term.

Accepted Answer

A) True 
 B)False

Question 7

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,hard drive capacity,and-monitor included (1=Yes,0=No).   Given this output,what is the variable,Monitor,called? Also,given the other variables in the model,is Monitor significant in explaining the variation in the dependent variable? Test using a .05 level of alpha.

Accepted Answer

The variable Monitor included is a quali

Question 8

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 PC's in the data set did not have a monitor included.

Accepted Answer

A) True 
 B)False

Question 9

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 10

A multiple regression is shown for a data set of yachts where the dependent variable is the price in thousands of dollars.   Based on this output,which of the independent variables appear to be significantly helping to predict the price of a yacht,using a 0.10 level of significance?

Accepted Answer

A) Age 
B) Age and length 
C) Rooms and Nav.Equip. 
D) Length and Nav.Equip. 
A) Age 
B) Age and length 
C) Rooms and Nav.Equip. 
D) Length and Nav.Equip.

Question 11

In simple linear regression analysis,the regression model forms a straight line in two-dimensional space through the x,y data points,while a multiple regression model forms a plane through multidimensional space.

Accepted Answer

A) True 
 B)False

Question 12

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

Accepted Answer

A) True 
 B)False

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:   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 14

A decision maker has five potential independent variables with which to build a regression model to explain the variation in the dependent variable.At step 1,variable x3 enters the regression model.Which of the following indicates which of the four remaining independent variables will be next to enter the model?

Accepted Answer

A) The variable that has the next highest correlation with the dependent variable 
B) The variable that will provide the next largest value for the slope coefficient 
C) The variable with the highest coefficient of partial determination 
D) Can't be determined without seeing the correlation matrix. 
A) The variable that has the next highest correlation with the dependent variable 
B) The variable that will provide the next largest value for the slope coefficient 
C) The variable with the highest coefficient of partial determination 
D) Can't be determined without seeing the correlation matrix.

Question 15

In a multiple regression model,the adjusted R-square value measures the explained variation in the dependent variable after taking into account the relationship between the sample size and the number of independent variables in the model.

Accepted Answer

A) True 
 B)False

Question 16

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 17

Where there are two independent variables in a multiple regression,the regression equation forms a plane.

Accepted Answer

A) True 
 B)False

Question 18

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 19

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 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.   Based on the above information,the test statistic for testing whether the overall model is statistically significant is approximately F = 17.45.

Accepted Answer

A) True 
 B)False

A standardized residual is:

When the best subsets approach is used in a regression application,one method for determining which of the many possible models to select for potential use is called the C_p statistic.

Consider the following regression model: = B₀ + B₁x₁ + + ε.If B₂ > 0,then the parabola will open downward and if B₂ < 0,then the parabola will open downward.

A multiple regression is shown for a data set of yachts where the dependent variable is the price in thousands of dollars. Given this information,what is the null hypothesis for testing the overall model?

When a regression equation includes a term such as x₁x₂ where two independent variables are multiplied,this is an interaction term.

A multiple regression is shown for a data set of yachts where the dependent variable is the price in thousands of dollars. Based on this output,which of the independent variables appear to be significantly helping to predict the price of a yacht,using a 0.10 level of significance?

In simple linear regression analysis,the regression model forms a straight line in two-dimensional space through the x,y data points,while a multiple regression model forms a plane through multidimensional space.

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

In a multiple regression model,the adjusted R-square value measures the explained variation in the dependent variable after taking into account the relationship between the sample size and the number of independent variables in the model.

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

Where there are two independent variables in a multiple regression,the regression equation forms a plane.

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

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

The Where, why, and How of Data Collection

Graphs,charts and Tablesdescribing Your Data

Describing Data Using Numerical Measures

Using Probability and Probability Distributions

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

Introduction to Decision Analysis

Filters

Exam 15: Multiple Regression Analysis and Model Building

A standardized residual is:

When the best subsets approach is used in a regression application,one method for determining which of the many possible models to select for potential use is called the Cp statistic.

Consider the following regression model: = B0 + B1x1 + + ε.If B2 > 0,then the parabola will open downward and if B2 < 0,then the parabola will open downward.

A multiple regression is shown for a data set of yachts where the dependent variable is the price in thousands of dollars. Given this information,what is the null hypothesis for testing the overall model?

When a regression equation includes a term such as x1x2 where two independent variables are multiplied,this is an interaction term.

A multiple regression is shown for a data set of yachts where the dependent variable is the price in thousands of dollars. Based on this output,which of the independent variables appear to be significantly helping to predict the price of a yacht,using a 0.10 level of significance?

In simple linear regression analysis,the regression model forms a straight line in two-dimensional space through the x,y data points,while a multiple regression model forms a plane through multidimensional space.

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

In a multiple regression model,the adjusted R-square value measures the explained variation in the dependent variable after taking into account the relationship between the sample size and the number of independent variables in the model.

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

Where there are two independent variables in a multiple regression,the regression equation forms a plane.

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

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

The Where, why, and How of Data Collection

Graphs,charts and Tablesdescribing Your Data

Describing Data Using Numerical Measures

Using Probability and Probability Distributions

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

Introduction to Decision Analysis

Filters

When the best subsets approach is used in a regression application,one method for determining which of the many possible models to select for potential use is called the C_p statistic.

Consider the following regression model: = B₀ + B₁x₁ + + ε.If B₂ > 0,then the parabola will open downward and if B₂ < 0,then the parabola will open downward.

When a regression equation includes a term such as x₁x₂ where two independent variables are multiplied,this is an interaction term.

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

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