Exam 15: Multiple Regression Analysis and Model Building

The method used in regression analysis for incorporating a categorical variable into the model is by organizing the categorical variable into one or more dummy variables.

(True/False)

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Question 101

In conducting multiple regression analysis,t-tests should be conducted prior to conducting the F-test.

(True/False)

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Question 102

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?

(Multiple Choice)

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Question 103

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.

(True/False)

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Question 104

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

(True/False)

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Question 105

In a forward stepwise regression process,it is actually possible for the R-square value to decline if variables are added to the regression model that do not help to explain the variation in the dependent variable.

(True/False)

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Question 106

The following residual plot was constructed based on a simple linear regression model. Based on this plot,there appears to be no basis for concluding that a curvilinear model may be more appropriate than a linear model to explain the variation in the y variable.

(True/False)

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Question 107

If one or more of the regression assumptions has been violated this means that the current regression model is not the best one for this data set,and another model should be sought.

(True/False)

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Question 108

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 critical value for testing the significance of the overall regression model at a 0.05 level of statistical significance?

(Multiple Choice)

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Question 109

Explain the difference between forward stepwise regression (standard stepwise),forward selection,and all possible subsets regression approaches.

(Essay)

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Question 110

Which of the following is not an assumption of the multiple regression model?

(Multiple Choice)

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Question 111

It is generally suggested that the sample size in developing a multiple regression model should be at least four times the number of independent variables.

(True/False)

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Question 112

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

(True/False)

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Question 113

The following multiple regression was conducted to attempt to predict the price of yachts based on the independent variables shown. Given this information and your knowledge of multiple regression,conduct the appropriate test to determine whether the overall regression model is statistically significant at the 0.05 level of significance using the critical value method.

(Essay)

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Question 114

The assumption that the errors or residuals are independent is best checked by:

(Multiple Choice)

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Question 115

The multiple coefficient of determination measures the percentage of variation in the dependent variable that is explained by the independent variables in the model.

(True/False)

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Question 116

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 adjusted R-square value for this model?

(Multiple Choice)

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Question 117

Which of the following is not considered to be a stepwise regression technique?

(Multiple Choice)

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Question 118

A regression model of the form: = + + + + is called a 3^rd order polynomial model.

(True/False)

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Question 119

The adjusted R² value can be larger or smaller that the R² values depending on the data set.

(True/False)

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Question 120

Showing 101 - 120 of 153

The method used in regression analysis for incorporating a categorical variable into the model is by organizing the categorical variable into one or more dummy variables.

In conducting multiple regression analysis,t-tests should be conducted prior to conducting the F-test.

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?

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.

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

In a forward stepwise regression process,it is actually possible for the R-square value to decline if variables are added to the regression model that do not help to explain the variation in the dependent variable.

The following residual plot was constructed based on a simple linear regression model. Based on this plot,there appears to be no basis for concluding that a curvilinear model may be more appropriate than a linear model to explain the variation in the y variable.

If one or more of the regression assumptions has been violated this means that the current regression model is not the best one for this data set,and another model should be sought.

Explain the difference between forward stepwise regression (standard stepwise),forward selection,and all possible subsets regression approaches.

Which of the following is not an assumption of the multiple regression model?

It is generally suggested that the sample size in developing a multiple regression model should be at least four times the number of independent variables.

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

The assumption that the errors or residuals are independent is best checked by:

The multiple coefficient of determination measures the percentage of variation in the dependent variable that is explained by the independent variables in the model.

Which of the following is not considered to be a stepwise regression technique?

A regression model of the form: = + + + + is called a 3^rd order polynomial model.

The adjusted R² value can be larger or smaller that the R² values depending on the data set.

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

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Exam 15: Multiple Regression Analysis and Model Building

The method used in regression analysis for incorporating a categorical variable into the model is by organizing the categorical variable into one or more dummy variables.

In conducting multiple regression analysis,t-tests should be conducted prior to conducting the F-test.

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?

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.

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

In a forward stepwise regression process,it is actually possible for the R-square value to decline if variables are added to the regression model that do not help to explain the variation in the dependent variable.

The following residual plot was constructed based on a simple linear regression model. Based on this plot,there appears to be no basis for concluding that a curvilinear model may be more appropriate than a linear model to explain the variation in the y variable.

If one or more of the regression assumptions has been violated this means that the current regression model is not the best one for this data set,and another model should be sought.

Explain the difference between forward stepwise regression (standard stepwise),forward selection,and all possible subsets regression approaches.

Which of the following is not an assumption of the multiple regression model?

It is generally suggested that the sample size in developing a multiple regression model should be at least four times the number of independent variables.

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

The assumption that the errors or residuals are independent is best checked by:

The multiple coefficient of determination measures the percentage of variation in the dependent variable that is explained by the independent variables in the model.

Which of the following is not considered to be a stepwise regression technique?

A regression model of the form: = + + + + is called a 3rd order polynomial model.

The adjusted R2 value can be larger or smaller that the R2 values depending on the data set.

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

A regression model of the form: = + + + + is called a 3^rd order polynomial model.

The adjusted R² value can be larger or smaller that the R² values depending on the data set.