Question 1

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 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 5% level B

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).

Accepted Answer

A) True 
 B)False  False

Question 3

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  True

Question 4

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

Accepted Answer

A)  0.0592 
B)  0.9138 
C)  0.1149 
D)  0.9559 
E)  1.0000 
A)  0.0592 
B)  0.9138 
C)  0.1149 
D)  0.9559 
E)  1.0000

Question 5

A multiple regression analysis produced the following output from Minitab. Regression Analysis: Y versus x1 and x2 
  S = 0.179449 R-Sq = 89.0% R-Sq(adj)= 87.8%
Analysis of Variance
  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)  at least one of the variable is 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 the only predictor variable significant at the 5% level 
D)  x2 is the only predictor variable significant at the 5% level 
E)  at least one of the variable is significant at 5% level

Question 6

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 7

The F value that is used to test for the overall significance of a multiple regression model is calculated by dividing the mean square regression (MSreg)by the mean square error (MSerr).

Accepted Answer

A) True 
 B)False

Question 8

A multiple regression analysis produced the following tables.     
Using $\alpha$ = 0.01 to test the null hypothesis H0: $\beta$ 1 = $\beta$ 2 = 0,the critical F value is ____.

Accepted Answer

A)  8.68 
B)  6.36 
C)  8.40 
D)  6.11 
E)  3.36 
A)  8.68 
B)  6.36 
C)  8.40 
D)  6.11 
E)  3.36

Question 9

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 response variable in this model is _______.

Accepted Answer

A)  heated area 
B)  number of bedrooms 
C)  market value 
D)  central heating 
E)  residential houses 
A)  heated area 
B)  number of bedrooms 
C)  market value 
D)  central heating 
E)  residential houses

Question 10

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 11

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

Accepted Answer

A) True 
 B)False

Question 12

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

Accepted Answer

A) True 
 B)False

Question 13

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 14

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 response variable in this model is _____.

Accepted Answer

A)  family size 
B)  expenditures on groceries 
C)  household income 
D)  suburban 
E)  household neighborhood 
A)  family size 
B)  expenditures on groceries 
C)  household income 
D)  suburban 
E)  household neighborhood

Question 15

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 16

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 17

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 18

The following ANOVA table is from a multiple regression analysis.   The number of independent variables in the analysis is __________.

Accepted Answer

A)  30 
B)  26 
C)  1 
D)  3 
E)  2 
A)  30 
B)  26 
C)  1 
D)  3 
E)  2

Question 19

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 20

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

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

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).

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

A multiple regression analysis produced the following output from Minitab. Regression Analysis: Y versus x₁ and x₂ S = 0.179449 R-Sq = 89.0% R-Sq(adj)= 87.8% Analysis of Variance These results indicate that ____________.

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 F value that is used to test for the overall significance of a multiple regression model is calculated by dividing the mean square regression (MS_reg)by the mean square error (MS_err).

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 response variable in this model is _______.

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

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

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

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 response variable in this model is _____.

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

The following ANOVA table is from a multiple regression analysis. The number of independent variables in the analysis is __________.

A multiple regression analysis produced the following tables. The sample size 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

A Nalysis 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

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

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).

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

A multiple regression analysis produced the following output from Minitab. Regression Analysis: Y versus x1 and x2 S = 0.179449 R-Sq = 89.0% R-Sq(adj)= 87.8% Analysis of Variance These results indicate that ____________.

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 F value that is used to test for the overall significance of a multiple regression model is calculated by dividing the mean square regression (MSreg)by the mean square error (MSerr).

A multiple regression analysis produced the following tables. Using α\alphaα = 0.01 to test the null hypothesis H0: β\betaβ 1 = β\betaβ 2 = 0,the critical F value is ____.

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 response variable in this model 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 ____.

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

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

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

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 response variable in this model is _____.

The following ANOVA table is from a multiple regression analysis. The value of the standard error of the estimate se 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. Using α\alphaα = 0.05 to test the null hypothesis H0: β\betaβ 1 = β\betaβ 2 = 0,the critical F value is ____.

The following ANOVA table is from a multiple regression analysis. The number of independent variables in the analysis is __________.

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

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

A Nalysis 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 output from Minitab. Regression Analysis: Y versus x₁ and x₂ S = 0.179449 R-Sq = 89.0% R-Sq(adj)= 87.8% Analysis of Variance These results indicate that ____________.

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 F value that is used to test for the overall significance of a multiple regression model is calculated by dividing the mean square regression (MS_reg)by the mean square error (MS_err).

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

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

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