Question 1

Using multidimensional scaling (MDS),objects may be positioned in terms of _____.

Accepted Answer

A)  objective space 
B)  ideal preferences 
C)  subjective space 
D)  all of the above 
E)  none of the above 
A)  objective space 
B)  ideal preferences 
C)  subjective space 
D)  all of the above 
E)  none of the above

Question 2

The technique used to provide a more simple and interpretable picture of the relationships between factors and variables is called _____.

Accepted Answer

A)  rotation 
B)  regression 
C)  resistance 
D)  principal components 
E)  residual analysis 
A)  rotation 
B)  regression 
C)  resistance 
D)  principal components 
E)  residual analysis

Question 3

_____ is a regression procedure in which the predictor variables enter or leave the regression equation one at a time.

Accepted Answer

A)  Forward selection 
B)  Backward elimination 
C)  Stepwise selection 
D)  Ad hoc selection 
E)  Random elimination 
A)  Forward selection 
B)  Backward elimination 
C)  Stepwise selection 
D)  Ad hoc selection 
E)  Random elimination

Question 4

Which of the researcher withholds one-fourth to one-third of the data to evaluate how well the regression equation will predict beyond the sample used to calculate the regression equation,it is using _____.

Accepted Answer

A)  cluster analysis 
B)  a holdout sample 
C)  factor loadings 
D)  collinearity 
E)  None of the above 
A)  cluster analysis 
B)  a holdout sample 
C)  factor loadings 
D)  collinearity 
E)  None of the above

Question 5

_____ are simple correlations between the variables and the factors.

Accepted Answer

A)  Eigenvalues 
B)  Factor loadings 
C)  Principal components 
D)  Communalities 
E)  Betas 
A)  Eigenvalues 
B)  Factor loadings 
C)  Principal components 
D)  Communalities 
E)  Betas

Question 6

The amount of variance a variable shares with all other variables included in the factor analysis is referred to as _____.

Accepted Answer

A)  communality 
B)  total variance 
C)  shared variance 
D)  percentage of variance 
E)  eigenvalue 
A)  communality 
B)  total variance 
C)  shared variance 
D)  percentage of variance 
E)  eigenvalue

Question 7

_____ variables are nominal variables that may be used as predictors or independent variables in regression analysis by coding them with the values 0 and 1.

Accepted Answer

A)  Interval 
B)  Categorical 
C)  Coefficient 
D)  Dummy 
E)  Beta 
A)  Interval 
B)  Categorical 
C)  Coefficient 
D)  Dummy 
E)  Beta

Question 8

Explain the difference between forward selection,backward elimination,and stepwise selection for the imputation of variables in a regression equation.

Accepted Answer

A regression equation can be built with

Question 9

Which of the following statistical techniques predicts or explains the value for a dependent variable using the values of independent variables?

Accepted Answer

A)  Factor analysis 
B)  Multivariate analysis of variance 
C)  Multiple regression 
D)  Multidimensional scaling 
E)  Discriminant analysis 
A)  Factor analysis 
B)  Multivariate analysis of variance 
C)  Multiple regression 
D)  Multidimensional scaling 
E)  Discriminant analysis

Question 10

Which of the following statements is not true about factor rotation?

Accepted Answer

A)  Through rotation, the factor matrix is transformed into a simpler one that is easier to interpret 
B)  Rotation affects the communalities and the percentage of total variance explained 
C)  Preferably, variables should load on only one factor 
D)  Different rotation methods may identify different factors 
E)  One rotation method is varimax 
A)  Through rotation, the factor matrix is transformed into a simpler one that is easier to interpret 
B)  Rotation affects the communalities and the percentage of total variance explained 
C)  Preferably, variables should load on only one factor 
D)  Different rotation methods may identify different factors 
E)  One rotation method is varimax

Question 11

The linear combinations of independent variables developed by discriminant analysis that will best discriminate between the categories of the dependent variable are _____.

Accepted Answer

A)  discriminant functions 
B)  discriminant scores 
C)  characteristic profiles 
D)  correlation coefficients 
E)  beta weights 
A)  discriminant functions 
B)  discriminant scores 
C)  characteristic profiles 
D)  correlation coefficients 
E)  beta weights

Question 12

In multidimensional scaling,the _____ is a lack of fit measure; higher values indicate poorer fits.

Accepted Answer

A)  beta weight 
B)  stress index 
C)  R2 
D)  X2 
E)  factor loading 
A)  beta weight 
B)  stress index 
C)  R2 
D)  X2 
E)  factor loading

Question 13

The most widely used structural equation modeling software program is _____.

Accepted Answer

A)  LISREL 
B)  EQS 
C)  Bartlett's VISIO 
D)  AMOS 
E)  JUMP 
A)  LISREL 
B)  EQS 
C)  Bartlett's VISIO 
D)  AMOS 
E)  JUMP

Question 14

Which of the following statistical techniques is appropriate when the variables to be analyzed are interrelated without designations as to whether they are criterion and predictor variables?

Accepted Answer

A)  Multiple regression 
B)  Multivariate analysis of variance 
C)  Discriminant analysis 
D)  Factor analysis 
E)  Path analysis 
A)  Multiple regression 
B)  Multivariate analysis of variance 
C)  Discriminant analysis 
D)  Factor analysis 
E)  Path analysis

Question 15

A _____ is a graphical device for displaying clusters and their relative distances.

Accepted Answer

A)  dendrogram 
B)  scatterplot 
C)  Pareto diagram 
D)  boxplot 
E)  line graph 
A)  dendrogram 
B)  scatterplot 
C)  Pareto diagram 
D)  boxplot 
E)  line graph

Question 16

Principal component analysis describes _____.

Accepted Answer

A)  a method for identifying the variables in multidimensional scaling 
B)  a method for identifying the variables in path analysis 
C)  a method for reducing the number of variables in a factor analysis 
D)  a method for reducing the number of variables in conjoint analysis 
E)  None of the above 
A)  a method for identifying the variables in multidimensional scaling 
B)  a method for identifying the variables in path analysis 
C)  a method for reducing the number of variables in a factor analysis 
D)  a method for reducing the number of variables in conjoint analysis 
E)  None of the above

Question 17

Which of the following statistical techniques identifies patterns underlying combinations of the original variables capable of summarizing the original set?

Accepted Answer

A)  Factor analysis 
B)  Multivariate analysis of variance 
C)  Cluster analysis 
D)  Multidimensional scaling 
E)  Discriminant analysis 
A)  Factor analysis 
B)  Multivariate analysis of variance 
C)  Cluster analysis 
D)  Multidimensional scaling 
E)  Discriminant analysis

Question 18

Which of the following is NOT a problem associated with multicollinearity?

Accepted Answer

A)  Estimated regression coefficients can fluctuate widely 
B)  It is difficult to assess the relative importance of the independent variables in explaining the variation in the dependent variables 
C)  Predictor variables may be incorrectly included or removed in stepwise regression 
D)  It becomes difficult to compute the correct test statistic 
E)  All of the above are problems caused by multicollinearity 
A)  Estimated regression coefficients can fluctuate widely 
B)  It is difficult to assess the relative importance of the independent variables in explaining the variation in the dependent variables 
C)  Predictor variables may be incorrectly included or removed in stepwise regression 
D)  It becomes difficult to compute the correct test statistic 
E)  All of the above are problems caused by multicollinearity

Question 19

_____ is a technique that attempts to determine the relative importance consumers attach to salient attributes and the utilities they attach to the levels of attributes.

Accepted Answer

A)  Discriminant analysis 
B)  Regression 
C)  MANOVA 
D)  Conjoint analysis 
E)  Factor analysis 
A)  Discriminant analysis 
B)  Regression 
C)  MANOVA 
D)  Conjoint analysis 
E)  Factor analysis

Question 20

Which of the following statements is FALSE?

Accepted Answer

A)  In cluster analysis, objects in each cluster tend to be similar to each other and dissimilar to objects in the other clusters 
B)  Cluster analysis is also called classification analysis or numerical taxonomy 
C)  Groups or clusters are suggested by the data, not defined a priori 
D)  Cluster analysis is appropriate when the criterion or dependent variable is categorical and the independent variables are interval 
E)  All of the above are true 
A)  In cluster analysis, objects in each cluster tend to be similar to each other and dissimilar to objects in the other clusters 
B)  Cluster analysis is also called classification analysis or numerical taxonomy 
C)  Groups or clusters are suggested by the data, not defined a priori 
D)  Cluster analysis is appropriate when the criterion or dependent variable is categorical and the independent variables are interval 
E)  All of the above are true

Exam 24: Appendix: Multivariate Supplement

Using multidimensional scaling (MDS),objects may be positioned in terms of _____.

The technique used to provide a more simple and interpretable picture of the relationships between factors and variables is called _____.

_____ is a regression procedure in which the predictor variables enter or leave the regression equation one at a time.

Which of the researcher withholds one-fourth to one-third of the data to evaluate how well the regression equation will predict beyond the sample used to calculate the regression equation,it is using _____.

_____ are simple correlations between the variables and the factors.

The amount of variance a variable shares with all other variables included in the factor analysis is referred to as _____.

_____ variables are nominal variables that may be used as predictors or independent variables in regression analysis by coding them with the values 0 and 1.

Explain the difference between forward selection,backward elimination,and stepwise selection for the imputation of variables in a regression equation.

Which of the following statistical techniques predicts or explains the value for a dependent variable using the values of independent variables?

Which of the following statements is not true about factor rotation?

The linear combinations of independent variables developed by discriminant analysis that will best discriminate between the categories of the dependent variable are _____.

In multidimensional scaling,the _____ is a lack of fit measure; higher values indicate poorer fits.

The most widely used structural equation modeling software program is _____.

Which of the following statistical techniques is appropriate when the variables to be analyzed are interrelated without designations as to whether they are criterion and predictor variables?

A _____ is a graphical device for displaying clusters and their relative distances.

Principal component analysis describes _____.

Which of the following statistical techniques identifies patterns underlying combinations of the original variables capable of summarizing the original set?

Which of the following is NOT a problem associated with multicollinearity?

_____ is a technique that attempts to determine the relative importance consumers attach to salient attributes and the utilities they attach to the levels of attributes.

Which of the following statements is FALSE?

Research in Business

Ethics in Business Research

Thinking Like a Researcher

The Research Process: an Overview

Clarifying the Research Question Through Secondary Data and Exploration

Research Design: An Overview

Qualitative Research

Observation Studies

Experiments

Surveys

Measurement

Measurement Scales

Questionnaires and Instruments

Sampling

Data Preparation and Description

Exploring,Displaying,and Examining Data

Hypothesis Testing

Measures of Association

Presenting Insights and Findings: Written Reports

Presenting Insights and Findings: Oral Presentations

Appendix 1A: How the Industry Works

Appendix 5A and 5B: Bibliographic Database Searchers and Advanced Searches

Appendix 9B: Test Markets

Filters