Question 1

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 2

In regression analysis,outliers may be identified by examining the ________.

Accepted Answer

A)  coefficient of determination 
B)  coefficient of correlation 
C)  p-values for the partial coefficients 
D)  residuals 
E)  R-squared value 
A)  coefficient of determination 
B)  coefficient of correlation 
C)  p-values for the partial coefficients 
D)  residuals 
E)  R-squared value

Question 3

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 4

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

Question 5

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 6

A multiple regression analysis produced the following tables.   
Using $\alpha$ = 0.05 to test the null hypothesis H0: $\beta$2 = 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 7

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

Accepted Answer

A)  1500 
B)  50 
C)  2300 
D)  500 
E)  31 
A)  1500 
B)  50 
C)  2300 
D)  500 
E)  31

Question 8

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 9

Multiple t-tests are used to determine whether the independent variables in the regression model are significant.

Accepted Answer

A) True 
 B)False

Question 10

Suppose that the regression equation y = c1 + 0.32 x1 + 0.41 x2 + 5.31 x3 predicts an adult's height (y)given the individual's mother's height (x1),his or her father's height (x2),and whether the individual is male (x3 = 1)or female (x3 = 0).All heights are measured in inches.Assume also that this equation is stable through time,the average adult female height is currently 63.8 inches and the average adult male height is 69.7 inches.If the average female height is stable through time (daughters are on average exactly as tall their mothers),then c1 = ______.

Accepted Answer

A)  There is not enough information to determine the average female height in two generations. 
B)  16.515 
C)  15.751 
D)  14.807 
E)  13.155 
A)  There is not enough information to determine the average female height in two generations. 
B)  16.515 
C)  15.751 
D)  14.807 
E)  13.155

Question 11

If we reject H0: β1= β2=0 using the F-test,then we should conclude that both slopes are different from zero.

Accepted Answer

A) True 
 B)False

Question 12

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

Accepted Answer

A)  y = 616.6849 + 3.33833 x1 + 1.780075 x2 
B)  y = 154.5535 - 1.43058 x1 + 5.30407 x2 
C)  y = 616.6849 - 3.33833 x1 - 1.780075 x2 
D)  y = 154.5535 + 2.333548 x1 + 0.335605 x2 
E)  y = 616.6849 - 3.33833 x1 + 1.780075 x2 
A)  y = 616.6849 + 3.33833 x1 + 1.780075 x2 
B)  y = 154.5535 - 1.43058 x1 + 5.30407 x2 
C)  y = 616.6849 - 3.33833 x1 - 1.780075 x2 
D)  y = 154.5535 + 2.333548 x1 + 0.335605 x2 
E)  y = 616.6849 - 3.33833 x1 + 1.780075 x2

Question 13

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 14

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 15

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 "number of employees at the plant" variable in this model is ______.

Accepted Answer

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

Question 16

Suppose that the regression equation y = 16.99 + 0.32 x1 + 0.41 x2 + 5.31 x3 predicts an adult's height (y)given the individual's mother's height (x1),his or her father's height (x2),and whether the individual is male (x3 = 1)or female (x3 = 0).All heights are measured in inches.In this equation,the coefficient of ______ means that ______.

Accepted Answer

A)  x2; if two individuals have fathers whose heights differ by 1 inch, then the individuals' heights will differ by 0.41 inches. 
B)  x2; if two individuals have mothers whose heights differ by 1 inch, then the individuals' heights will differ by 0.41 inches. 
C)  x3; a brother is expected to be 5.31 inches taller than his sister 
D)  x1; if two individuals have mothers whose heights differ by 0.32 inch, then the individuals' heights will differ by 1 inch. 
E)  x1; if two individuals have mothers whose heights differ by 0.5 inch, then the individuals' heights will differ by 0.32 inch. 
A)  x2; if two individuals have fathers whose heights differ by 1 inch, then the individuals' heights will differ by 0.41 inches. 
B)  x2; if two individuals have mothers whose heights differ by 1 inch, then the individuals' heights will differ by 0.41 inches. 
C)  x3; a brother is expected to be 5.31 inches taller than his sister 
D)  x1; if two individuals have mothers whose heights differ by 0.32 inch, then the individuals' heights will differ by 1 inch. 
E)  x1; if two individuals have mothers whose heights differ by 0.5 inch, then the individuals' heights will differ by 0.32 inch.

Question 17

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 18

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 19

The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables.   The 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 20

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

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

In regression analysis,outliers may be identified by examining the ________.

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 ____________.

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

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

Multiple t-tests are used to determine whether the independent variables in the regression model are significant.

If we reject H₀: β₁= β₂=0 using the F-test,then we should conclude that both slopes are different from zero.

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

A multiple regression analysis produced the following tables. For x₁= 360 and x₂ = 220,the predicted value of y 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 "central heating" variable in this model is _______.

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

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

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

In regression analysis,outliers may be identified by examining the ________.

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 ____________.

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

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

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

Multiple t-tests are used to determine whether the independent variables in the regression model are significant.

If we reject H0: β1= β2=0 using the F-test,then we should conclude that both slopes are different from zero.

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

A multiple regression analysis produced the following tables. For x1= 360 and x2 = 220,the predicted value of y 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 "central heating" variable in this model is _______.

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

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

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

If we reject H₀: β₁= β₂=0 using the F-test,then we should conclude that both slopes are different from zero.

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

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

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

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