Question 1

The following ANOVA table is from a multiple regression analysis.   The adjusted R2 value is __________.

Accepted Answer

A) 0.65 
B) 0.39 
C) 0.61 
D) 0.53 
E) 0.78 
A) 0.65 
B) 0.39 
C) 0.61 
D) 0.53 
E) 0.78 C

Question 2

A multiple regression analysis produced the following tables.     
Using $\alpha$ = 0.05 to test the null hypothesis H0: $\beta$1 = 0,the critical t value is ____.

Accepted Answer

A) ± 1.753 
B) ± 2.110 
C) ± 2.131 
D) ± 1.740 
E) ± 2.500 
A) ± 1.753 
B) ± 2.110 
C) ± 2.131 
D) ± 1.740 
E) ± 2.500 C

Question 3

The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables.   The MSR value is __________.

Accepted Answer

A) 700.00 
B) 350.00 
C) 233.33 
D) 175.00 
E) 275.00 
A) 700.00 
B) 350.00 
C) 233.33 
D) 175.00 
E) 275.00 D

Question 4

A slope in a multiple regression model is known as a partial slope because it ignores the effects of other explanatory variables.

Accepted Answer

A) True 
 B)False

Question 5

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch),production plant (Kingsland,and Yorktown),and production shift (day,and evening).The response variable in this model is ______.

Accepted Answer

A) batch size 
B) production shift 
C) production plant 
D) total cost 
E) variable cost 
A) batch size 
B) production shift 
C) production plant 
D) total cost 
E) variable cost

Question 6

A multiple regression analysis produced the following tables.     The adjusted R2 is ____________.

Accepted Answer

A) 0.9138 
B) 0.9408 
C) 0.8981 
D) 0.8851 
E) 0.8891 
A) 0.9138 
B) 0.9408 
C) 0.8981 
D) 0.8851 
E) 0.8891

Question 7

A multiple regression analysis produced the following tables.     These results indicate that ____________.

Accepted Answer

A) none of the predictor variables are significant at the 5% level 
B) each predictor variable is significant at the 5% level 
C) x1 is significant at the 5% level 
D) x2 is significant at the 5% level 
E) the intercept is not significant at 5% level 
A) none of the predictor variables are significant at the 5% level 
B) each predictor variable is significant at the 5% level 
C) x1 is significant at the 5% level 
D) x2 is significant at the 5% level 
E) the intercept is not significant at 5% level

Question 8

A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size,household income,and household neighborhood (urban,suburban,and rural).The "neighborhood" variable in this model is ______.

Accepted Answer

A) an independent variable 
B) a response variable 
C) a quantitative variable 
D) a dependent variable 
E) a constant 
A) an independent variable 
B) a response variable 
C) a quantitative variable 
D) a dependent variable 
E) a constant

Question 9

A multiple regression analysis produced the following tables.     For x1= 40 and x2 = 90,the predicted value of y is ____________.

Accepted Answer

A) 753.77 
B) 1,173.00 
C) 1,355.26 
D) 3,719.39 
E) 1,565.75 
A) 753.77 
B) 1,173.00 
C) 1,355.26 
D) 3,719.39 
E) 1,565.75

Question 10

In the multiple regression model y = $\beta$ 0 + $\beta$ 1x1 + $\beta$ 2x2 + $\beta$ 3x3 + $\varepsilon$,the $\beta$ coefficients of the x variables are called partial regression coefficients.

Accepted Answer

A) True 
 B)False

Question 11

The multiple regression formulas used to estimate the regression coefficients are designed to ________________.

Accepted Answer

A) minimize the total sum of squares (SST) 
B) minimize the sum of squares of error (SS
E)  
C) maximize the standard error of the estimate 
D) maximize the p-value for the calculated F value 
E) minimize the mean error 
A) minimize the total sum of squares (SST) 
B) minimize the sum of squares of error (SS
E)  
C) maximize the standard error of the estimate 
D) maximize the p-value for the calculated F value 
E) minimize the mean error

Question 12

A multiple regression analysis produced the following tables.     These results indicate that ____________.

Accepted Answer

A) none of the predictor variables are significant at the 5% level 
B) each predictor variable is significant at the 5% level 
C) x1 is the only predictor variable significant at the 5% level 
D) x2 is the only predictor variable significant at the 5% level 
E) the intercept is not significant at the 5% level 
A) none of the predictor variables are significant at the 5% level 
B) each predictor variable is significant at the 5% level 
C) x1 is the only predictor variable significant at the 5% level 
D) x2 is the only predictor variable significant at the 5% level 
E) the intercept is not significant at the 5% level

Question 13

A multiple regression analysis produced the following tables.     For x1= 30 and x2 = 100,the predicted value of y is ____________.

Accepted Answer

A) 753.77 
B) 1,173.00 
C) 1,355.26 
D) 615.13 
E) 6153.13 
A) 753.77 
B) 1,173.00 
C) 1,355.26 
D) 615.13 
E) 6153.13

Question 14

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch),production plant (Kingsland,and Yorktown),and production shift (day,and evening).In this model,"shift" is ______.

Accepted Answer

A) a response variable 
B) an independent variable 
C) a quantitative variable 
D) a dependent variable 
E) a constant 
A) a response variable 
B) an independent variable 
C) a quantitative variable 
D) a dependent variable 
E) a constant

Question 15

The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables.   The number of degrees of freedom for error is __________.

Accepted Answer

A) 1 
B) 4 
C) 34 
D) 30 
E) 35 
A) 1 
B) 4 
C) 34 
D) 30 
E) 35

Question 16

A multiple regression analysis produced the following tables.     The adjusted R2 is ____________.

Accepted Answer

A) 0.2079 
B) 0.0860 
C) 0.5440 
D) 0.7921 
E) 1.0000 
A) 0.2079 
B) 0.0860 
C) 0.5440 
D) 0.7921 
E) 1.0000

Question 17

Minitab and Excel output for a multiple regression model show the t tests for the regression coefficients but do not provide a t test for the regression constant.

Accepted Answer

A) True 
 B)False

Question 18

The following ANOVA table is from a multiple regression analysis.   The value of the standard error of the estimate se is __________.

Accepted Answer

A) 30.77 
B) 5.55 
C) 4.03 
D) 3.20 
E) 0.73 
A) 30.77 
B) 5.55 
C) 4.03 
D) 3.20 
E) 0.73

Question 19

A multiple regression analysis produced the following tables.   
Using $\alpha$ = 0.01 to test the model,these results indicate that ____________.

Accepted Answer

A) at least one of the regression variables is a significant predictor of y 
B) none of the regression variables are significant predictors of y 
C) y cannot be sufficiently predicted using these data 
D) y is a good predictor of the regression variables in the model 
E) the y intercept in this model is the best predictor variable 
A) at least one of the regression variables is a significant predictor of y 
B) none of the regression variables are significant predictors of y 
C) y cannot be sufficiently predicted using these data 
D) y is a good predictor of the regression variables in the model 
E) the y intercept in this model is the best predictor variable

Question 20

A human resources analyst is developing a regression model to predict electricity production plant manager compensation as a function of production capacity of the plant,number of employees at the plant,and plant technology (coal,oil,and nuclear).The "plant technology" variable in this model is ______.

Accepted Answer

A) a response variable 
B) a dependent variable 
C) a quantitative variable 
D) an independent variable 
E) a constant 
A) a response variable 
B) a dependent variable 
C) a quantitative variable 
D) an independent variable 
E) a constant

The following ANOVA table is from a multiple regression analysis. The adjusted R2 value is __________.

The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables. The MSR value is __________.

A slope in a multiple regression model is known as a partial slope because it ignores the effects of other explanatory variables.

A multiple regression analysis produced the following tables. The adjusted R² is ____________.

A multiple regression analysis produced the following tables. These results indicate that ____________.

A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size,household income,and household neighborhood (urban,suburban,and rural).The "neighborhood" variable in this model is ______.

A multiple regression analysis produced the following tables. For x1= 40 and x2 = 90,the predicted value of y is ____________.

In the multiple regression model y = $\beta$ 0 + $\beta$ 1x1 + $\beta$ 2x2 + $\beta$ 3x3 + $\varepsilon$ ,the $\beta$ coefficients of the x variables are called partial regression coefficients.

The multiple regression formulas used to estimate the regression coefficients are designed to ________________.

A multiple regression analysis produced the following tables. These results indicate that ____________.

A multiple regression analysis produced the following tables. For x1= 30 and x2 = 100,the predicted value of y is ____________.

The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables. The number of degrees of freedom for error is __________.

A multiple regression analysis produced the following tables. The adjusted R² is ____________.

Minitab and Excel output for a multiple regression model show the t tests for the regression coefficients but do not provide a t test for the regression constant.

The following ANOVA table is from a multiple regression analysis. The value of the standard error of the estimate se is __________.

A multiple regression analysis produced the following tables. $A multiple regression analysis produced the following tables. Using \alpha = 0.01 to test the model,these results indicate that .$ Using $\alpha$ = 0.01 to test the model,these results indicate that .

Introduction to Statistics

Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Continuous Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Simple Regression Analysis and Correlation

Building Multiple Regression Models

Time-Series Forecasting and Index Numbers

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

Filters

Exam 13: Multiple Regression Analysis

The following ANOVA table is from a multiple regression analysis. The adjusted R2 value is __________.

A multiple regression analysis produced the following tables. Using α\alphaα = 0.05 to test the null hypothesis H0: β\betaβ 1 = 0,the critical t value is ____.

The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables. The MSR value is __________.

A slope in a multiple regression model is known as a partial slope because it ignores the effects of other explanatory variables.

A multiple regression analysis produced the following tables. The adjusted R2 is ____________.

A multiple regression analysis produced the following tables. These results indicate that ____________.

A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size,household income,and household neighborhood (urban,suburban,and rural).The "neighborhood" variable in this model is ______.

A multiple regression analysis produced the following tables. For x1= 40 and x2 = 90,the predicted value of y is ____________.

In the multiple regression model y = β\betaβ 0 + β\betaβ 1x1 + β\betaβ 2x2 + β\betaβ 3x3 + ε\varepsilonε ,the β\betaβ coefficients of the x variables are called partial regression coefficients.

The multiple regression formulas used to estimate the regression coefficients are designed to ________________.

A multiple regression analysis produced the following tables. These results indicate that ____________.

A multiple regression analysis produced the following tables. For x1= 30 and x2 = 100,the predicted value of y is ____________.

The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables. The number of degrees of freedom for error is __________.

A multiple regression analysis produced the following tables. The adjusted R2 is ____________.

Minitab and Excel output for a multiple regression model show the t tests for the regression coefficients but do not provide a t test for the regression constant.

The following ANOVA table is from a multiple regression analysis. The value of the standard error of the estimate se is __________.

A multiple regression analysis produced the following tables. Using α\alphaα = 0.01 to test the model,these results indicate that ____________.

Introduction to Statistics

Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Continuous Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Simple Regression Analysis and Correlation

Building Multiple Regression Models

Time-Series Forecasting and Index Numbers

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

Filters

A multiple regression analysis produced the following tables. The adjusted R² is ____________.

In the multiple regression model y = $\beta$ 0 + $\beta$ 1x1 + $\beta$ 2x2 + $\beta$ 3x3 + $\varepsilon$ ,the $\beta$ coefficients of the x variables are called partial regression coefficients.

A multiple regression analysis produced the following tables. The adjusted R² is ____________.

A multiple regression analysis produced the following tables. $A multiple regression analysis produced the following tables. Using \alpha = 0.01 to test the model,these results indicate that .$ Using $\alpha$ = 0.01 to test the model,these results indicate that .