Question 1

Time series data often exhibits which of the following characteristics?

Accepted Answer

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

Question 2

There are situations where a set of explanatory variables forms a logical group.The test to determine whether the extra variables provide enough extra explanatory power to warrant inclusion in the equation is referred to as the:

Accepted Answer

A) complete F-test 
B) reduced F-test 
C) partial F-test 
D) reduced t-test 
A) complete F-test 
B) reduced F-test 
C) partial F-test 
D) reduced t-test

Question 3

In regression analysis,the total variation in the dependent variable Y,measured by   and referred to as SST,can be decomposed into two parts: the explained variation,measured by SSR,and the unexplained variation,measured by SSE.

Accepted Answer

A) True 
 B)False

Question 4

In testing the overall fit of a multiple regression model in which there are three explanatory variables,the null hypothesis is   .

Accepted Answer

A) True 
 B)False

Question 5

In multiple regression,the problem of multicollinearity affects the t-tests of the individual coefficients as well as the F-test in the analysis of variance for regression,since the F-test combines these t-tests into a single test.

Accepted Answer

A) True 
 B)False

Question 6

The _____ can be used to test for autocorrelation.

Accepted Answer

A) regression coefficient 
B) correlation coefficient 
C) Durbin-Watson statistic 
D) F-test or t-test 
A) regression coefficient 
B) correlation coefficient 
C) Durbin-Watson statistic 
D) F-test or t-test

Question 7

The appropriate hypothesis test for a regression coefficient is:

Accepted Answer

A)    
B)    
C)    
D) None of these options 
A)    
B)    
C)    
D) None of these options

Question 8

(A)Estimate a multiple regression model using all of the available explanatory variables.
(B)Conduct and interpret the result of an F- test on the given model.Employ a 5% level of significance in conducting this statistical hypothesis test.
(C)Is there evidence of autocorrelated residuals in this model? Explain why or why not.

Accepted Answer

(A) @#IMG-DLM& The multiple regression model (wher

Question 9

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 10

A backward procedure is a type of equation building procedure that begins with all potential explanatory variables in the regression equation and deletes them two at a time until further deletion would reduce the percentage of variation explained to a value less than 0.50.

Accepted Answer

A) True 
 B)False

Question 11

In a multiple regression problem involving 30 observations and four explanatory variables,SST = 800 and SSE = 240.The value of the F-statistic for testing the significance of this model is 14.583.

Accepted Answer

A) True 
 B)False

Question 12

One method of diagnosing heteroscedasticity is to plot the residuals against the predicted values of Y,then look for a change in the spread of the plotted values.

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 
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 
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

If you can determine that the outlier is not really a member of the relevant population,then it is appropriate and probably best to:

Accepted Answer

A) average it 
B) reduce it 
C) delete it 
D) leave it 
A) average it 
B) reduce it 
C) delete it 
D) leave it

Question 15

The appropriate hypothesis test for an ANOVA test is:

Accepted Answer

A)    
B)    
C)    
D)    
A)    
B)    
C)    
D)

Question 16

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 17

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 18

The term autocorrelation refers to:

Accepted Answer

A) analyzed data refers to itself 
B) sample is related too closely to the population 
C) data are in a loop (values repeat themselves) 
D) time series variables are usually related to their own past values 
A) analyzed data refers to itself 
B) sample is related too closely to the population 
C) data are in a loop (values repeat themselves) 
D) time series variables are usually related to their own past values

Question 19

A point that "tilts" the regression line toward it,is referred to as a(n):

Accepted Answer

A) magnetic point 
B) influential point 
C) extreme point 
D) explanatory point 
A) magnetic point 
B) influential point 
C) extreme point 
D) explanatory point

Question 20

If the partial F test indicates that a group of variables is significant,it also implies that each variable in the group is significant.

Accepted Answer

A) True 
 B)False

Time series data often exhibits which of the following characteristics?

There are situations where a set of explanatory variables forms a logical group.The test to determine whether the extra variables provide enough extra explanatory power to warrant inclusion in the equation is referred to as the:

In regression analysis,the total variation in the dependent variable Y,measured by and referred to as SST,can be decomposed into two parts: the explained variation,measured by SSR,and the unexplained variation,measured by SSE.

In testing the overall fit of a multiple regression model in which there are three explanatory variables,the null hypothesis is .

In multiple regression,the problem of multicollinearity affects the t-tests of the individual coefficients as well as the F-test in the analysis of variance for regression,since the F-test combines these t-tests into a single test.

The _____ can be used to test for autocorrelation.

The appropriate hypothesis test for a regression coefficient is:

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.

A backward procedure is a type of equation building procedure that begins with all potential explanatory variables in the regression equation and deletes them two at a time until further deletion would reduce the percentage of variation explained to a value less than 0.50.

In a multiple regression problem involving 30 observations and four explanatory variables,SST = 800 and SSE = 240.The value of the F-statistic for testing the significance of this model is 14.583.

One method of diagnosing heteroscedasticity is to plot the residuals against the predicted values of Y,then look for a change in the spread of the plotted values.

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

If you can determine that the outlier is not really a member of the relevant population,then it is appropriate and probably best to:

The appropriate hypothesis test for an ANOVA test is:

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

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 term autocorrelation refers to:

A point that "tilts" the regression line toward it,is referred to as a(n):

If the partial F test indicates that a group of variables is significant,it also implies that each variable in the group is significant.

Introduction to Data Analysis and Decision Making

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 Modeling: Applications

Introduction to Simulation Modeling

Simulation Models

Filters

Exam 11: Regression Analysis: Statistical Inference

Time series data often exhibits which of the following characteristics?

There are situations where a set of explanatory variables forms a logical group.The test to determine whether the extra variables provide enough extra explanatory power to warrant inclusion in the equation is referred to as the:

In regression analysis,the total variation in the dependent variable Y,measured by and referred to as SST,can be decomposed into two parts: the explained variation,measured by SSR,and the unexplained variation,measured by SSE.

In testing the overall fit of a multiple regression model in which there are three explanatory variables,the null hypothesis is .

In multiple regression,the problem of multicollinearity affects the t-tests of the individual coefficients as well as the F-test in the analysis of variance for regression,since the F-test combines these t-tests into a single test.

The _____ can be used to test for autocorrelation.

The appropriate hypothesis test for a regression coefficient is:

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.

A backward procedure is a type of equation building procedure that begins with all potential explanatory variables in the regression equation and deletes them two at a time until further deletion would reduce the percentage of variation explained to a value less than 0.50.

In a multiple regression problem involving 30 observations and four explanatory variables,SST = 800 and SSE = 240.The value of the F-statistic for testing the significance of this model is 14.583.

One method of diagnosing heteroscedasticity is to plot the residuals against the predicted values of Y,then look for a change in the spread of the plotted values.

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

If you can determine that the outlier is not really a member of the relevant population,then it is appropriate and probably best to:

The appropriate hypothesis test for an ANOVA test is:

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

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 term autocorrelation refers to:

A point that "tilts" the regression line toward it,is referred to as a(n):

If the partial F test indicates that a group of variables is significant,it also implies that each variable in the group is significant.

Introduction to Data Analysis and Decision Making

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 Modeling: Applications

Introduction to Simulation Modeling

Simulation Models

Filters