Question 1

Dummy or indicator variables typically are values of zero or one,and are used to model the effects of different levels of ___________ variables.

Accepted Answer

A)  qualitative 
B)  quantitative 
C)  ratio 
D)  measured 
A)  qualitative 
B)  quantitative 
C)  ratio 
D)  measured

Question 2

To avoid overfitting in a neural network model,the parameter estimates that are used minimize the least squares criterion.

Accepted Answer

A) True 
 B)False

Question 3

Testing the contribution of individual independent variables with ttests is performed prior to the Ftest for the model in multiple regression analysis.

Accepted Answer

A) True 
 B)False

Question 4

The mean square error of a multiple regression model with k independent variables and n observations is __________.

Accepted Answer

A)  SSE/n 
B)  SSE/[n + (k+1)] 
C)  SSE/[n− (k+1)] 
D)  SSE/(k+1) 
A)  SSE/n 
B)  SSE/[n + (k+1)] 
C)  SSE/[n− (k+1)] 
D)  SSE/(k+1)

Question 5

In a multiple regression model,the residuals were plotted against the values of one of the independent variables.The plot exhibited a funneling out pattern of residuals.This means that as the value of the independent variable increases,the error terms tend to ___________ and the model assumption of __________ is violated.

Accepted Answer

A)  increase,constant variance 
B)  increase,independence 
C)  decrease,constant variance 
D)  decrease,normality 
A)  increase,constant variance 
B)  increase,independence 
C)  decrease,constant variance 
D)  decrease,normality

Question 6

In a regression model,at any given combination of values of the independent variables,the population of potential error terms is assumed to have an F distribution.

Accepted Answer

A) True 
 B)False

Question 7

A major drawback of neural network modeling is that its parameters are usually uninterpretable.

Accepted Answer

A) True 
 B)False

Question 8

The primary use of stepwise regression is to identify the most important ___________ that should be included in the multiple regression model.

Accepted Answer

A)  independent variables 
B)  dependent variables 
C)  dummy variables 
D)  quadratic variables 
A)  independent variables 
B)  dependent variables 
C)  dummy variables 
D)  quadratic variables

Question 9

In a multiple regression mode,if the largest variance inflation factor (VIF)is 21.6,then it can be concluded that there are indications of multicollinearity.

Accepted Answer

A) True 
 B)False

Question 10

Even when an unimportant variable is added to a regression model,the explained variation will increase.

Accepted Answer

A) True 
 B)False

Question 11

Using squared and interaction variables in a multiple regression model results in extreme multicollinearity.

Accepted Answer

A) True 
 B)False

Question 12

The penalty weight used in the neural network models controls the tradeoff between overfitting and underfitting.

Accepted Answer

A) True 
 B)False

Question 13

The range of feasible values for the multiple coefficient of determination is from ________.

Accepted Answer

A)  0 to 
B)  −1 to 0 
C)  −1 to 1 
D)  0 to 1 
E)  - 
A)  0 to 
B)  −1 to 0 
C)  −1 to 1 
D)  0 to 1 
E)  -

Question 14

An investigator hired by a client suing for sex discrimination has developed a multiple regression model for employee salaries for the company in question.In this multiple regression model,the salaries are in thousands of dollars.For example,a data entry of 35 for the dependent variable indicates a salary of $35,000.The indicator (dummy)variable for gender is coded as X1 = 0 if male and X1 = 1 if female.The computer output of this multiple regression model shows that the coefficient for this variable (X1)is −4.2.The t test showed that X1 was significant at α= 0.1.This result implies that for male and female workers of the company,

Accepted Answer

A)  on the average,females earn $4,200 less. 
B)  on the average,males earn $4,200 less. 
C)  on the average,salaries do not differ. 
D)  on the average,males have 4.2 more years of experience. 
E)  on the average,females have 4.2 more years of experience. 
A)  on the average,females earn $4,200 less. 
B)  on the average,males earn $4,200 less. 
C)  on the average,salaries do not differ. 
D)  on the average,males have 4.2 more years of experience. 
E)  on the average,females have 4.2 more years of experience.

Question 15

The multiple coefficient of determination is the _______ divided by the total variation

Accepted Answer

A)  unexplained variation 
B)  SSE 
C)  explained variation 
D)  distance value 
E)  leverage value 
A)  unexplained variation 
B)  SSE 
C)  explained variation 
D)  distance value 
E)  leverage value

Question 16

In the quadratic regression model y = β0 + β1X1 + β2X12 + ε,the β2 term represents the

Accepted Answer

A)  rate of curvature of the parabola. 
B)  value of Y when X is zero. 
C)  shift parameter of the parabola. 
D)  y-intercept of the parabola. 
A)  rate of curvature of the parabola. 
B)  value of Y when X is zero. 
C)  shift parameter of the parabola. 
D)  y-intercept of the parabola.

Question 17

___________ is an iterative variable selection procedure that allows an independent variable to be added to a multiple regression model in one iteration and deleted during the next iteration.

Accepted Answer

A)  Logistic regression 
B)  Stepwise regression 
C)  Quadratic regression 
D)  Backward regression 
A)  Logistic regression 
B)  Stepwise regression 
C)  Quadratic regression 
D)  Backward regression

Question 18

A regression technique for analyzing large data sets is neural network modeling.

Accepted Answer

A) True 
 B)False

Question 19

The ____________ term describes the effects on y of all factors other than the independent variables in a multiple regression model.

Accepted Answer

A)  dependent 
B)  t test 
C)  error 
D)  dummy 
A)  dependent 
B)  t test 
C)  error 
D)  dummy

Question 20

A studentized residual for an observation that is greater than 2 in absolute value is evidence that the observation is an outlier.

Accepted Answer

A) True 
 B)False

Dummy or indicator variables typically are values of zero or one,and are used to model the effects of different levels of ___________ variables.

To avoid overfitting in a neural network model,the parameter estimates that are used minimize the least squares criterion.

Testing the contribution of individual independent variables with ttests is performed prior to the Ftest for the model in multiple regression analysis.

The mean square error of a multiple regression model with k independent variables and n observations is __________.

In a regression model,at any given combination of values of the independent variables,the population of potential error terms is assumed to have an F distribution.

A major drawback of neural network modeling is that its parameters are usually uninterpretable.

The primary use of stepwise regression is to identify the most important ___________ that should be included in the multiple regression model.

In a multiple regression mode,if the largest variance inflation factor (VIF)is 21.6,then it can be concluded that there are indications of multicollinearity.

Even when an unimportant variable is added to a regression model,the explained variation will increase.

Using squared and interaction variables in a multiple regression model results in extreme multicollinearity.

The penalty weight used in the neural network models controls the tradeoff between overfitting and underfitting.

The range of feasible values for the multiple coefficient of determination is from ________.

The multiple coefficient of determination is the _______ divided by the total variation

In the quadratic regression model y = β₀ + β₁X₁ + β₂X₁² + ε,the β₂ term represents the

___________ is an iterative variable selection procedure that allows an independent variable to be added to a multiple regression model in one iteration and deleted during the next iteration.

A regression technique for analyzing large data sets is neural network modeling.

The ____________ term describes the effects on y of all factors other than the independent variables in a multiple regression model.

A studentized residual for an observation that is greater than 2 in absolute value is evidence that the observation is an outlier.

An Introduction to Business Statistics

Descriptive Statistics: Tabular and Graphical Methods

Descriptive Statistics: Numerical Methods

Probability

Discrete Random Variables

Continuous Random Variables

Sampling and Sampling Distributions

Confidence Intervals

Hypothesis Testing

Statistical Inferences for Means and Proportions

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Multiple Regression and Model Building

Time Series Forecasting and Index Numbers

Nonparametric Methods

Decision Theory

Filters

Exam 14: Simple Linear Regression Analysis

Dummy or indicator variables typically are values of zero or one,and are used to model the effects of different levels of ___________ variables.

To avoid overfitting in a neural network model,the parameter estimates that are used minimize the least squares criterion.

Testing the contribution of individual independent variables with ttests is performed prior to the Ftest for the model in multiple regression analysis.

The mean square error of a multiple regression model with k independent variables and n observations is __________.

In a regression model,at any given combination of values of the independent variables,the population of potential error terms is assumed to have an F distribution.

A major drawback of neural network modeling is that its parameters are usually uninterpretable.

The primary use of stepwise regression is to identify the most important ___________ that should be included in the multiple regression model.

In a multiple regression mode,if the largest variance inflation factor (VIF)is 21.6,then it can be concluded that there are indications of multicollinearity.

Even when an unimportant variable is added to a regression model,the explained variation will increase.

Using squared and interaction variables in a multiple regression model results in extreme multicollinearity.

The penalty weight used in the neural network models controls the tradeoff between overfitting and underfitting.

The range of feasible values for the multiple coefficient of determination is from ________.

The multiple coefficient of determination is the _______ divided by the total variation

In the quadratic regression model y = β0 + β1X1 + β2X12 + ε,the β2 term represents the

___________ is an iterative variable selection procedure that allows an independent variable to be added to a multiple regression model in one iteration and deleted during the next iteration.

A regression technique for analyzing large data sets is neural network modeling.

The ____________ term describes the effects on y of all factors other than the independent variables in a multiple regression model.

A studentized residual for an observation that is greater than 2 in absolute value is evidence that the observation is an outlier.

An Introduction to Business Statistics

Descriptive Statistics: Tabular and Graphical Methods

Descriptive Statistics: Numerical Methods

Probability

Discrete Random Variables

Continuous Random Variables

Sampling and Sampling Distributions

Confidence Intervals

Hypothesis Testing

Statistical Inferences for Means and Proportions

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Multiple Regression and Model Building

Time Series Forecasting and Index Numbers

Nonparametric Methods

Decision Theory

Filters

In the quadratic regression model y = β₀ + β₁X₁ + β₂X₁² + ε,the β₂ term represents the