Question 1

Another term for constant error variance is:

Accepted Answer

A)  homoscedasticity 
B)  heteroscedasticity 
C)  autocorrelation 
D)  multicollinearity 
A)  homoscedasticity 
B)  heteroscedasticity 
C)  autocorrelation 
D)  multicollinearity

Question 2

In regression analysis, extrapolation is performed when you:

Accepted Answer

A)  attempt to predict beyond the limits of the sample 
B)  have to estimate some of the explanatory variable values 
C)  have to use a lag variable as an explanatory variable in the model 
D)  do not have observations for every period in the sample 
A)  attempt to predict beyond the limits of the sample 
B)  have to estimate some of the explanatory variable values 
C)  have to use a lag variable as an explanatory variable in the model 
D)  do not have observations for every period in the sample

Question 3

The Durbin-Watson statistic can be used to test for autocorrelation.

Accepted Answer

A) True 
 B)False

Question 4

A confidence interval constructed around a point prediction from a regression model is called a prediction interval, because the actual point being estimated is not a population parameter.

Accepted Answer

A) True 
 B)False

Question 5

The assumptions of regression are: 1) there is a population regression line, 2) the dependent variable is normally distributed, 3) the standard deviation of the response variable remains constant as the explanatory variables increase, and 4) the errors are probabilistically independent.

Accepted Answer

A) True 
 B)False

Question 6

Suppose you forecast the values of all of the independent variables and insert them into a multiple regression equation and obtain a point prediction for the dependent variable. You could then use the standard error of the estimate to obtain an approximate:

Accepted Answer

A)  confidence interval 
B)  prediction interval 
C)  hypothesis test 
D)  independence test 
A)  confidence interval 
B)  prediction interval 
C)  hypothesis test 
D)  independence test

Question 7

In simple linear regression, if the error variable   is normally distributed, the test statistic for testing   is t-distributed with n - 2 degrees of freedom.

Accepted Answer

A) True 
 B)False

Question 8

In time series data, errors are often not probabilistically independent.

Accepted Answer

A) True 
 B)False

Question 9

The ANOVA table splits the total variation into two parts. They are the:

Accepted Answer

A)  acceptable and unacceptable variation 
B)  adequate and inadequate variation 
C)  resolved and unresolved variation 
D)  explained and unexplained variation 
A)  acceptable and unacceptable variation 
B)  adequate and inadequate variation 
C)  resolved and unresolved variation 
D)  explained and unexplained variation

Question 10

Many statistical packages have three types of equation-building procedures. They are:

Accepted Answer

A)  forward, linear, and non-linear 
B)  forward, backward, and stepwise 
C)  simple, complex, and stepwise 
D)  inclusion, exclusion, and linear 
A)  forward, linear, and non-linear 
B)  forward, backward, and stepwise 
C)  simple, complex, and stepwise 
D)  inclusion, exclusion, and linear

Question 11

Which of the following is the relevant sampling distribution for regression coefficients?

Accepted Answer

A)  normal distribution 
B)  t-distribution with n-1 degrees of freedom 
C)  t-distribution with n-1-k degrees of freedom 
D)  F-distribution with n-1-k degrees of freedom 
A)  normal distribution 
B)  t-distribution with n-1 degrees of freedom 
C)  t-distribution with n-1-k degrees of freedom 
D)  F-distribution with n-1-k degrees of freedom

Question 12

When there is a group of explanatory variables that are in some sense logically related, all of them must be included in the regression equation.

Accepted Answer

A) True 
 B)False

Question 13

Which of the following is not one of the assumptions of regression?

Accepted Answer

A)  There is a population regression line that joins the SDs of all possible distributions of results. 
B)  The response variable is normally distributed. 
C)  The standard deviation of the response variable increases as the explanatory variables increase. 
D)  The errors are probabilistically independent. 
A)  There is a population regression line that joins the SDs of all possible distributions of results. 
B)  The response variable is normally distributed. 
C)  The standard deviation of the response variable increases as the explanatory variables increase. 
D)  The errors are probabilistically independent.

Question 14

When determining whether to include or exclude a variable in regression analysis, if the p-value associated with the variable's t-value is above some accepted significance value, such as 0.05, then the variable:

Accepted Answer

A)  is a candidate for inclusion 
B)  is a candidate for exclusion 
C)  is redundant 
D)  does not fit the guidelines of parsimony 
A)  is a candidate for inclusion 
B)  is a candidate for exclusion 
C)  is redundant 
D)  does not fit the guidelines of parsimony

Question 15

The objective typically used in the tree types of equation-building procedures is to:

Accepted Answer

A)  find the equation with a small se 
B)  find the equation with a large R2 
C)  find the equation with a small se and a large R2 
D)  find the equation with the smallest F-ratio 
A)  find the equation with a small se 
B)  find the equation with a large R2 
C)  find the equation with a small se and a large R2 
D)  find the equation with the smallest F-ratio

Question 16

Suppose that one equation has 3 explanatory variables and an F-ratio of 49. Another equation has 5 explanatory variables and an F-ratio of 38. The first equation will always be considered a better model.

Accepted Answer

A) True 
 B)False

Question 17

Do you see any problems evident in the plot below of residuals versus fitted values from a multiple regression analysis? Explain your answer.

Accepted Answer

There are a few points with la

Question 18

A forward procedure is a type of equation building procedure that begins with only one explanatory variable in the regression equation and successively adds one variable at a time until no remaining variables make a significant contribution.

Accepted Answer

A) True 
 B)False

Question 19

The residuals are observations of the error variable   . Consequently, the minimized sum of squared deviations is called the sum of squared error, labeled SSE.

Accepted Answer

A) True 
 B)False

Question 20

There is evidence that the regression equation provides little explanatory power when the F-ratio:

Accepted Answer

A)  is large 
B)  equals the regression coefficient 
C)  is small 
D)  is the constant 
A)  is large 
B)  equals the regression coefficient 
C)  is small 
D)  is the constant

Another term for constant error variance is:

In regression analysis, extrapolation is performed when you:

The Durbin-Watson statistic can be used to test for autocorrelation.

A confidence interval constructed around a point prediction from a regression model is called a prediction interval, because the actual point being estimated is not a population parameter.

The assumptions of regression are: 1) there is a population regression line, 2) the dependent variable is normally distributed, 3) the standard deviation of the response variable remains constant as the explanatory variables increase, and 4) the errors are probabilistically independent.

Suppose you forecast the values of all of the independent variables and insert them into a multiple regression equation and obtain a point prediction for the dependent variable. You could then use the standard error of the estimate to obtain an approximate:

In simple linear regression, if the error variable is normally distributed, the test statistic for testing is t-distributed with n - 2 degrees of freedom.

In time series data, errors are often not probabilistically independent.

The ANOVA table splits the total variation into two parts. They are the:

Many statistical packages have three types of equation-building procedures. They are:

Which of the following is the relevant sampling distribution for regression coefficients?

When there is a group of explanatory variables that are in some sense logically related, all of them must be included in the regression equation.

Which of the following is not one of the assumptions of regression?

When determining whether to include or exclude a variable in regression analysis, if the p-value associated with the variable's t-value is above some accepted significance value, such as 0.05, then the variable:

The objective typically used in the tree types of equation-building procedures is to:

Suppose that one equation has 3 explanatory variables and an F-ratio of 49. Another equation has 5 explanatory variables and an F-ratio of 38. The first equation will always be considered a better model.

Do you see any problems evident in the plot below of residuals versus fitted values from a multiple regression analysis? Explain your answer.

A forward procedure is a type of equation building procedure that begins with only one explanatory variable in the regression equation and successively adds one variable at a time until no remaining variables make a significant contribution.

The residuals are observations of the error variable . Consequently, the minimized sum of squared deviations is called the sum of squared error, labeled SSE.

There is evidence that the regression equation provides little explanatory power when the F-ratio:

Introduction to Business Analytics

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, Binomial, Poisson, and Exponential Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Estimating Relationships

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Models

Introduction to Simulation Modeling

Simulation Models

Data Mining

Importing Data Into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

Exam 11: Regression Analysis: Statistical Inference

Another term for constant error variance is:

In regression analysis, extrapolation is performed when you:

The Durbin-Watson statistic can be used to test for autocorrelation.

A confidence interval constructed around a point prediction from a regression model is called a prediction interval, because the actual point being estimated is not a population parameter.

The assumptions of regression are: 1) there is a population regression line, 2) the dependent variable is normally distributed, 3) the standard deviation of the response variable remains constant as the explanatory variables increase, and 4) the errors are probabilistically independent.

Suppose you forecast the values of all of the independent variables and insert them into a multiple regression equation and obtain a point prediction for the dependent variable. You could then use the standard error of the estimate to obtain an approximate:

In simple linear regression, if the error variable is normally distributed, the test statistic for testing is t-distributed with n - 2 degrees of freedom.

In time series data, errors are often not probabilistically independent.

The ANOVA table splits the total variation into two parts. They are the:

Many statistical packages have three types of equation-building procedures. They are:

Which of the following is the relevant sampling distribution for regression coefficients?

When there is a group of explanatory variables that are in some sense logically related, all of them must be included in the regression equation.

Which of the following is not one of the assumptions of regression?

When determining whether to include or exclude a variable in regression analysis, if the p-value associated with the variable's t-value is above some accepted significance value, such as 0.05, then the variable:

The objective typically used in the tree types of equation-building procedures is to:

Suppose that one equation has 3 explanatory variables and an F-ratio of 49. Another equation has 5 explanatory variables and an F-ratio of 38. The first equation will always be considered a better model.

Do you see any problems evident in the plot below of residuals versus fitted values from a multiple regression analysis? Explain your answer.

A forward procedure is a type of equation building procedure that begins with only one explanatory variable in the regression equation and successively adds one variable at a time until no remaining variables make a significant contribution.

The residuals are observations of the error variable . Consequently, the minimized sum of squared deviations is called the sum of squared error, labeled SSE.

There is evidence that the regression equation provides little explanatory power when the F-ratio:

Introduction to Business Analytics

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, Binomial, Poisson, and Exponential Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Estimating Relationships

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Models

Introduction to Simulation Modeling

Simulation Models

Data Mining

Importing Data Into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Filters