Question 1

In the model y = $\beta$ 0 + $\beta$ 1x1 + $\beta$ 2x2 + $\beta$ 3x3 + $\varepsilon$ ,y is the independent variable.

Accepted Answer

A) True 
 B)False

Question 2

In a multiple regression analysis with N observations and k independent variables,the degrees of freedom for the residual error is given by (N - k - 1).

Accepted Answer

A) True 
 B)False

Question 3

A real estate appraiser is developing a regression model to predict the market value of single family residential houses as a function of heated area,number of bedrooms,number of bathrooms,age of the house,and central heating (yes,no).The "central heating" variable in this model 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 4

A multiple regression analysis produced the following tables.     The sample size for this analysis is ____________.

Accepted Answer

A) 19 
B) 17 
C) 34 
D) 15 
E) 18 
A) 19 
B) 17 
C) 34 
D) 15 
E) 18

Question 5

A multiple regression analysis produced the following tables.     The coefficient of multiple determination is ____________.

Accepted Answer

A) 0.2079 
B) 0.0860 
C) 0.5440 
D) 0.7921 
E) 0.5000 
A) 0.2079 
B) 0.0860 
C) 0.5440 
D) 0.7921 
E) 0.5000

Question 6

A multiple regression analysis produced the following tables.   The sample size for this analysis is ____________.

Accepted Answer

A) 12 
B) 15 
C) 17 
D) 18 
E) 24 
A) 12 
B) 15 
C) 17 
D) 18 
E) 24

Question 7

The F value that is used to test for the overall significance of a multiple regression model is calculated by dividing the sum of mean squares regression (SSreg)by the sum of squares error (SSerr).

Accepted Answer

A) True 
 B)False

Question 8

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,"batch size" is ______.

Accepted Answer

A) a response variable 
B) an indicator variable 
C) a dependent variable 
D) a qualitative variable 
E) an independent variable 
A) a response variable 
B) an indicator variable 
C) a dependent variable 
D) a qualitative variable 
E) an independent variable

Question 9

The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables.   The adjusted R2 value is __________.

Accepted Answer

A) 0.80 
B) 0.70 
C) 0.66 
D) 0.76 
E) 0.30 
A) 0.80 
B) 0.70 
C) 0.66 
D) 0.76 
E) 0.30

Question 10

A multiple regression analysis produced the following tables.    
 Using $\alpha$ = 0.01 to test the null hypothesis H0: $\beta$2 = 0,the critical t value is ____.

Accepted Answer

A) ± 1.174 
B) ± 2.093 
C) ± 2.131 
D) ± 4.012 
E) ± 3.012 
A) ± 1.174 
B) ± 2.093 
C) ± 2.131 
D) ± 4.012 
E) ± 3.012

Question 11

The value of adjusted R2 always goes up when a nontrivial explanatory variable is added to a regression model.

Accepted Answer

A) True 
 B)False

Question 12

A multiple regression analysis produced the following tables.   For x1= 360 and x2 = 220,the predicted value of y is ____________.

Accepted Answer

A) 1314.70 
B) 1959.71 
C) 1077.58 
D) 2635.19 
E) 2265.57 
A) 1314.70 
B) 1959.71 
C) 1077.58 
D) 2635.19 
E) 2265.57

Question 13

A multiple regression analysis produced the following tables.     
Using $\alpha$ = 0.05 to test the null hypothesis H0: $\beta$1 = $\beta$2 = 0,the critical F value is ____.

Accepted Answer

A) 3.74 
B) 3.89 
C) 4.75 
D) 4.60 
E) 2.74 
A) 3.74 
B) 3.89 
C) 4.75 
D) 4.60 
E) 2.74

Question 14

The F test is used to determine whether the overall regression model is significant.

Accepted Answer

A) True 
 B)False

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 regression 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

The standard error of the estimate of a multiple regression model is essentially the standard deviation of the residuals for the regression model.

Accepted Answer

A) True 
 B)False

Question 17

A multiple regression analysis produced the following tables.     
Using $\alpha$ = 0.10 to test the null hypothesis H0: $\beta$2 = 0,the critical t value is ____.

Accepted Answer

A) ±1.345 
B) ±1.356 
C) ±1.761 
D) ±2.782 
E) ±1.782 
A) ±1.345 
B) ±1.356 
C) ±1.761 
D) ±2.782 
E) ±1.782

Question 18

A multiple regression analysis produced the following tables.     The regression equation for this analysis is ____________.

Accepted Answer

A) y = 302689 + 1153309 x1 + 1455998 x2 
B) y = -139.609 + 24.24619 x1 + 32.10171 x2 
C) y = 2548.989 + 22.25267 x1 + 17.44559 x2 
D) y = -0.05477 + 1.089586 x1 + 1.840105 x2 
E) y = 0.05477 + 1.089586 x1 + 1.840105 x2 
A) y = 302689 + 1153309 x1 + 1455998 x2 
B) y = -139.609 + 24.24619 x1 + 32.10171 x2 
C) y = 2548.989 + 22.25267 x1 + 17.44559 x2 
D) y = -0.05477 + 1.089586 x1 + 1.840105 x2 
E) y = 0.05477 + 1.089586 x1 + 1.840105 x2

Question 19

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

Accepted Answer

A) fail to reject the null hypothesis 
B) reject the null hypothesis 
C) fail to reject the alternative hypothesis 
D) reject the alternative hypothesis 
E) there is not enought information provided to make a decision 
A) fail to reject the null hypothesis 
B) reject the null hypothesis 
C) fail to reject the alternative hypothesis 
D) reject the alternative hypothesis 
E) there is not enought information provided to make a decision

Question 20

A multiple regression analysis produced the following tables.   The regression equation for this analysis is ____________.

Accepted Answer

A) y = 1959.71 + 0.46 x1 + 2.16 x2 
B) y = 1959.71 - 0.46 x1 + 2.16 x2 
C) y = 1959.71 - 0.46 x1 - 2.16 x2 
D) y =1959.71 + 0.46 x1 - 2.16 x2 
E) y =- 0.46 x1 - 2.16 x2 
A) y = 1959.71 + 0.46 x1 + 2.16 x2 
B) y = 1959.71 - 0.46 x1 + 2.16 x2 
C) y = 1959.71 - 0.46 x1 - 2.16 x2 
D) y =1959.71 + 0.46 x1 - 2.16 x2 
E) y =- 0.46 x1 - 2.16 x2

In the model y = $\beta$ 0 + $\beta$ 1x1 + $\beta$ 2x2 + $\beta$ 3x3 + $\varepsilon$ ,y is the independent variable.

In a multiple regression analysis with N observations and k independent variables,the degrees of freedom for the residual error is given by (N - k - 1).

A real estate appraiser is developing a regression model to predict the market value of single family residential houses as a function of heated area,number of bedrooms,number of bathrooms,age of the house,and central heating (yes,no).The "central heating" variable in this model is _______.

A multiple regression analysis produced the following tables. The sample size for this analysis is ____________.

A multiple regression analysis produced the following tables. The coefficient of multiple determination is ____________.

A multiple regression analysis produced the following tables. The sample size for this analysis is ____________.

The F value that is used to test for the overall significance of a multiple regression model is calculated by dividing the sum of mean squares regression (SS_reg)by the sum of squares error (SS_err).

The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables. The adjusted R2 value is __________.

The value of adjusted R² always goes up when a nontrivial explanatory variable is added to a regression model.

A multiple regression analysis produced the following tables. For x1= 360 and x2 = 220,the predicted value of y is ____________.

The F test is used to determine whether the overall regression model is significant.

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

The standard error of the estimate of a multiple regression model is essentially the standard deviation of the residuals for the regression model.

A multiple regression analysis produced the following tables. The regression equation for this analysis is ____________.

A multiple regression analysis produced the following tables. The regression equation for this analysis is ____________.

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

In the model y = β\betaβ 0 + β\betaβ 1x1 + β\betaβ 2x2 + β\betaβ 3x3 + ε\varepsilonε ,y is the independent variable.

In a multiple regression analysis with N observations and k independent variables,the degrees of freedom for the residual error is given by (N - k - 1).

A real estate appraiser is developing a regression model to predict the market value of single family residential houses as a function of heated area,number of bedrooms,number of bathrooms,age of the house,and central heating (yes,no).The "central heating" variable in this model is _______.

A multiple regression analysis produced the following tables. The sample size for this analysis is ____________.

A multiple regression analysis produced the following tables. The coefficient of multiple determination is ____________.

A multiple regression analysis produced the following tables. The sample size for this analysis is ____________.

The F value that is used to test for the overall significance of a multiple regression model is calculated by dividing the sum of mean squares regression (SSreg)by the sum of squares error (SSerr).

The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables. The adjusted R2 value is __________.

A multiple regression analysis produced the following tables. Using α\alphaα = 0.01 to test the null hypothesis H0: β\betaβ 2 = 0,the critical t value is ____.

The value of adjusted R2 always goes up when a nontrivial explanatory variable is added to a regression model.

A multiple regression analysis produced the following tables. For x1= 360 and x2 = 220,the predicted value of y is ____________.

A multiple regression analysis produced the following tables. Using α\alphaα = 0.05 to test the null hypothesis H0: β\betaβ 1 = β\betaβ 2 = 0,the critical F value is ____.

The F test is used to determine whether the overall regression model is significant.

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

The standard error of the estimate of a multiple regression model is essentially the standard deviation of the residuals for the regression model.

A multiple regression analysis produced the following tables. Using α\alphaα = 0.10 to test the null hypothesis H0: β\betaβ 2 = 0,the critical t value is ____.

A multiple regression analysis produced the following tables. The regression equation for this analysis 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 correct decision is ____.

A multiple regression analysis produced the following tables. The regression equation for this analysis is ____________.

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

In the model y = $\beta$ 0 + $\beta$ 1x1 + $\beta$ 2x2 + $\beta$ 3x3 + $\varepsilon$ ,y is the independent variable.

The F value that is used to test for the overall significance of a multiple regression model is calculated by dividing the sum of mean squares regression (SS_reg)by the sum of squares error (SS_err).

The value of adjusted R² always goes up when a nontrivial explanatory variable is added to a regression model.