Question 1

In an ANOVA table for a multiple regression analysis, total variation is separated into _________.

Accepted Answer

A) Treatment and error variation 
B) Regression and residual variation 
C) Treatment and block variation 
D) Block and error variation 
A) Treatment and error variation 
B) Regression and residual variation 
C) Treatment and block variation 
D) Block and error variation

Question 2

A correlation matrix can be used to assess multicollinearity between independent variables.

Accepted Answer

A) True 
 B)False

Question 3

How are residual plots drawn and used to evaluate the assumptions of linear multiple regression?

Accepted Answer

A residual plot graphs the residuals aga

Question 4

A multiple regression analysis showed the following ANOVA table result.   Based on the information in the ANOVA, what is the decision regarding the global null hypothesis?

Accepted Answer

Reject the null hypothesis; th

Question 5

Twenty-one executives in a large corporation were randomly selected to study the effect of several factors on annual salary (expressed in $000s). The factors selected were age, seniority, years of college, number of company divisions they had been exposed to, and the level of their responsibility. The results of the regression analysis follow:   Which independent variable has the most significant effect on annual salary?

Accepted Answer

Level of r

Question 6

In an ANOVA table, for a multiple regression analysis, the variation of the dependent variable explained by the variation of the independent variables is represented by ___________.

Accepted Answer

A) The regression sum of squares 
B) The total sum of squares 
C) The residual mean square 
D) The p-value 
A) The regression sum of squares 
B) The total sum of squares 
C) The residual mean square 
D) The p-value

Question 7

In multiple regression analysis, a correlation matrix is used to check for ___________.

Accepted Answer

The answer of In multiple regression analysis, a correlation matrix...

Question 8

In multiple regression analysis, when the independent variables are highly correlated, this situation is called __________________.

Accepted Answer

A) Autocorrelation 
B) Multicollinearity 
C) Homoscedasticity 
D) Curvilinearity 
A) Autocorrelation 
B) Multicollinearity 
C) Homoscedasticity 
D) Curvilinearity

Question 9

What does the correlation matrix for a multiple regression analysis contain?

Accepted Answer

A) Multiple correlation coefficients 
B) Simple correlation coefficients 
C) Multiple coefficients of determination 
D) Multiple standard errors of estimate 
A) Multiple correlation coefficients 
B) Simple correlation coefficients 
C) Multiple coefficients of determination 
D) Multiple standard errors of estimate

Question 10

Twenty-one executives in a large corporation were randomly selected to study the effect of several factors on annual salary (expressed in $000s). The factors selected were age, seniority, years of college, number of company divisions they had been exposed to, and the level of their responsibility. The results of the regression analysis follow:   Test the hypothesis that the regression coefficient for age is equal to 0 at the 0.05 significance level. Report the degrees of freedom, the critical value, the test-statistic, and your decision.

Accepted Answer

d.f. = 15; t-critica

Question 11

If the hypothesis H0: β1= 0, is rejected, then the sample regression coefficient b1 indicates the change in the predicted value for a unit change in X1 when all other Xi variables are held constant.

Accepted Answer

A) True 
 B)False

Question 12

The best example of a null hypothesis for testing an individual regression coefficient is __________.

Accepted Answer

A) H0: β1 = β2 = β3 = β4 = 0 
B) H0: µ1 = µ2 = µ3 = µ4 = 0 
C) H0: β1 = 0 
D) H0: β1 ≠ 0 
A) H0: β1 = β2 = β3 = β4 = 0 
B) H0: µ1 = µ2 = µ3 = µ4 = 0 
C) H0: β1 = 0 
D) H0: β1 ≠ 0

Question 13

If a dependent variable and one of the independent variables are inversely related, the sign for the regression coefficient of the independent variable is ____________.

Accepted Answer

The answer of If a dependent variable and one of...

Question 14

In multiple regression, a dummy variable is significantly related to the dependent variable when ______________.

Accepted Answer

A) The global test of the regression equation is rejected 
B) The test of the dummy variable's regression coefficient is rejected 
C) The dummy variable is correlated with other independent variables 
D) The dummy variable is coded as 2 or 3 
A) The global test of the regression equation is rejected 
B) The test of the dummy variable's regression coefficient is rejected 
C) The dummy variable is correlated with other independent variables 
D) The dummy variable is coded as 2 or 3

Question 15

A __________ analysis is used to develop an equation that predicts an outcome based on two or more independent variables.

Accepted Answer

The answer of A __________ analysis is used to develop...

Question 16

When applying stepwise regression, the basis for including an independent variable in a multiple regression model is __________.

Accepted Answer

The greatest increase of expla

Question 17

How are scatter diagrams used to evaluate the assumptions of linear multiple regression?

Accepted Answer

A scatter diagram can be used to evaluat

Question 18

A researcher is studying the effect of 10 different variables on a critical measure of business performance. In selecting the best set of independent variables to predict the dependent variable, the stepwise regression technique is used. How are variables selected for inclusion in the model?

Accepted Answer

A) Highest increase in the multiple R2 
B) Largest p-value 
C) Smallest p-value 
D) Smallest regression coefficient 
A) Highest increase in the multiple R2 
B) Largest p-value 
C) Smallest p-value 
D) Smallest regression coefficient

Question 19

What are the five assumptions of linear multiple regression?

Accepted Answer

(1) A linear relationship between the de

Question 20

Stepwise regression analysis is a method that assists in selecting the most significant variables for a multiple regression equation.

Accepted Answer

A) True 
 B)False

In an ANOVA table for a multiple regression analysis, total variation is separated into _________.

A correlation matrix can be used to assess multicollinearity between independent variables.

How are residual plots drawn and used to evaluate the assumptions of linear multiple regression?

A multiple regression analysis showed the following ANOVA table result. Based on the information in the ANOVA, what is the decision regarding the global null hypothesis?

In an ANOVA table, for a multiple regression analysis, the variation of the dependent variable explained by the variation of the independent variables is represented by ___________.

In multiple regression analysis, a correlation matrix is used to check for ___________.

In multiple regression analysis, when the independent variables are highly correlated, this situation is called __________________.

What does the correlation matrix for a multiple regression analysis contain?

If the hypothesis H₀: β₁= 0, is rejected, then the sample regression coefficient b₁ indicates the change in the predicted value for a unit change in X₁ when all other X_i variables are held constant.

The best example of a null hypothesis for testing an individual regression coefficient is __________.

If a dependent variable and one of the independent variables are inversely related, the sign for the regression coefficient of the independent variable is ____________.

In multiple regression, a dummy variable is significantly related to the dependent variable when ______________.

A __________ analysis is used to develop an equation that predicts an outcome based on two or more independent variables.

When applying stepwise regression, the basis for including an independent variable in a multiple regression model is __________.

How are scatter diagrams used to evaluate the assumptions of linear multiple regression?

A researcher is studying the effect of 10 different variables on a critical measure of business performance. In selecting the best set of independent variables to predict the dependent variable, the stepwise regression technique is used. How are variables selected for inclusion in the model?

What are the five assumptions of linear multiple regression?

Stepwise regression analysis is a method that assists in selecting the most significant variables for a multiple regression equation.

What Is Statistics

Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation

Describing Data: Numerical Measures

Describing Data: Displaying and Exploring Data

A Survey of Probability Concepts

Discrete Probability Distributions

Continuous Probability Distributions

Sampling Methods and the Central Limit Theorem

Estimation and Confidence Intervals

One-Sample Tests of Hypothesis

Two-Sample Tests of Hypothesis

Analysis of Variance

Correlation and Linear Regression

Nonparametric Methods: Goodness-Of-Fit Tests

Filters

Exam 14: Multiple Regression Analysis

In an ANOVA table for a multiple regression analysis, total variation is separated into _________.

A correlation matrix can be used to assess multicollinearity between independent variables.

How are residual plots drawn and used to evaluate the assumptions of linear multiple regression?

A multiple regression analysis showed the following ANOVA table result. Based on the information in the ANOVA, what is the decision regarding the global null hypothesis?

In an ANOVA table, for a multiple regression analysis, the variation of the dependent variable explained by the variation of the independent variables is represented by ___________.

In multiple regression analysis, a correlation matrix is used to check for ___________.

In multiple regression analysis, when the independent variables are highly correlated, this situation is called __________________.

What does the correlation matrix for a multiple regression analysis contain?

If the hypothesis H0: β1= 0, is rejected, then the sample regression coefficient b1 indicates the change in the predicted value for a unit change in X1 when all other Xi variables are held constant.

The best example of a null hypothesis for testing an individual regression coefficient is __________.

If a dependent variable and one of the independent variables are inversely related, the sign for the regression coefficient of the independent variable is ____________.

In multiple regression, a dummy variable is significantly related to the dependent variable when ______________.

A __________ analysis is used to develop an equation that predicts an outcome based on two or more independent variables.

When applying stepwise regression, the basis for including an independent variable in a multiple regression model is __________.

How are scatter diagrams used to evaluate the assumptions of linear multiple regression?

A researcher is studying the effect of 10 different variables on a critical measure of business performance. In selecting the best set of independent variables to predict the dependent variable, the stepwise regression technique is used. How are variables selected for inclusion in the model?

What are the five assumptions of linear multiple regression?

Stepwise regression analysis is a method that assists in selecting the most significant variables for a multiple regression equation.

What Is Statistics

Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation

Describing Data: Numerical Measures

Describing Data: Displaying and Exploring Data

A Survey of Probability Concepts

Discrete Probability Distributions

Continuous Probability Distributions

Sampling Methods and the Central Limit Theorem

Estimation and Confidence Intervals

One-Sample Tests of Hypothesis

Two-Sample Tests of Hypothesis

Analysis of Variance

Correlation and Linear Regression

Nonparametric Methods: Goodness-Of-Fit Tests

Filters

If the hypothesis H₀: β₁= 0, is rejected, then the sample regression coefficient b₁ indicates the change in the predicted value for a unit change in X₁ when all other X_i variables are held constant.