Question 1

A is a lower triangle matrix showing the simple correlations, r, between all possible pairs of variables included in the analysis.

Accepted Answer

A)  factor matrix 
B)  classification matrix 
C)  total correlation matrix 
D)  correlation matrix 
A)  factor matrix 
B)  classification matrix 
C)  total correlation matrix 
D)  correlation matrix

Question 2

The factors identified in factor analysis are overtly observed in the population.

Accepted Answer

A) True 
 B)False

Question 3

Factor analysis is somewhat similar to discriminant analysis in that each variable is expressed as a linear combination of underlying factors.

Accepted Answer

A) True 
 B)False

Question 4

A _ is a plot of the original variables using the factor loadings as coordinates.

Accepted Answer

A)  scree plot 
B)  scattergram 
C)  factor loading plot 
D)  territorial map 
A)  scree plot 
B)  scattergram 
C)  factor loading plot 
D)  territorial map

Question 5

Which of the following applications is appropriate for using factor analysis?

Accepted Answer

A)  to understand the media consumption habits of the target market 
B)  to determine if variation in market share can be accounted for by the size of the sales force and advertising expenditures 
C)  to identify the characteristics of price- sensitive consumers 
D)  Both A and C are correct. 
A)  to understand the media consumption habits of the target market 
B)  to determine if variation in market share can be accounted for by the size of the sales force and advertising expenditures 
C)  to identify the characteristics of price- sensitive consumers 
D)  Both A and C are correct.

Question 6

Which statement is not true about principal components analysis (PCA)?

Accepted Answer

A)  The total variance in the data is considered. 
B)  PCA is recommended when the primary concern is to determine the minimum number of factors that will account for maximum variance in the data for use in subsequent multivariate analysis. 
C)  The factors are estimated based only on the common variance. 
D)  The diagonal of the correlation matrix consist of unities. 
A)  The total variance in the data is considered. 
B)  PCA is recommended when the primary concern is to determine the minimum number of factors that will account for maximum variance in the data for use in subsequent multivariate analysis. 
C)  The factors are estimated based only on the common variance. 
D)  The diagonal of the correlation matrix consist of unities.

Question 7

A factor model that provides a good fit to the data has many large residuals.

Accepted Answer

A) True 
 B)False

Question 8

The various methods of factor analysis are differentiated by the approach used to derive the weights or factor score coefficients.

Accepted Answer

A) True 
 B)False

Question 9

Which is not a method of factor analysis?

Accepted Answer

A)  common factor analysis 
B)  omega method 
C)  unweighted least squares 
D)  principal components analysis 
A)  common factor analysis 
B)  omega method 
C)  unweighted least squares 
D)  principal components analysis

Question 10

It is recommended that the factors extracted should account for at least of the variance.

Accepted Answer

A)  50 % 
B)  60% 
C)  65% 
D)  70% 
A)  50 % 
B)  60% 
C)  65% 
D)  70%

Question 11

It is possible to compute as many principal components as there are variables; in doing so, parsimony is gained.

Accepted Answer

A) True 
 B)False

Question 12

Factor loadings represent the correlations between sets of variables.

Accepted Answer

A) True 
 B)False

Question 13

Bartlett's test of sphericity is one test of the appropriateness of the factor model.

Accepted Answer

A) True 
 B)False

Question 14

When selecting surrogate variables from variables with similarly high loadings, the choice should be based on _ .

Accepted Answer

A)  theoretical considerations 
B)  measurement considerations 
C)  the variable with the highest loading on a factor 
D)  Both A and B are correct 
A)  theoretical considerations 
B)  measurement considerations 
C)  the variable with the highest loading on a factor 
D)  Both A and B are correct

Question 15

Generally, the number of factors determined by a scree plot will be one or a few less than that determined by the eigenvalue criterion.

Accepted Answer

A) True 
 B)False

Question 16

What are the steps involved in conducting factor analysis (Figure 19.3 in the text)?

Accepted Answer

The steps involved in conducting factor

Question 17

Communality is .

Accepted Answer

A)  the amount of variance a variable shares with all the other variables being considered 
B)  the percentage of the total variance attributed to each factor 
C)  the proportion of variance explained by the common factors 
D)  both A and C are correct 
A)  the amount of variance a variable shares with all the other variables being considered 
B)  the percentage of the total variance attributed to each factor 
C)  the proportion of variance explained by the common factors 
D)  both A and C are correct

Question 18

Which method of analysis does not classify variables as dependent or independent?

Accepted Answer

A)  discriminant analysis 
B)  regression analysis 
C)  analysis of variance 
D)  factor analysis 
A)  discriminant analysis 
B)  regression analysis 
C)  analysis of variance 
D)  factor analysis

Question 19

If the variables are standardized, the factor model may be presented as .

Accepted Answer

A)  Xi = Ai1 F1 + Ai2 F2 + Ai3 F3 + ... + Aim Fm + ViUi 
B)  Fi = Wi1 X1 + Wi2 X2 + Wi3 X3 + ... + Wim Xm + ViUi 
C)  Xi = Wi1 F1 + Wi2 F2 + Wi3 F3 + ... + Wim Fm + ViUi 
D)  Xi = Ai1 F1 + Ai2 F2 + Ai3 F3 + ... + Aim Fm 
A)  Xi = Ai1 F1 + Ai2 F2 + Ai3 F3 + ... + Aim Fm + ViUi 
B)  Fi = Wi1 X1 + Wi2 X2 + Wi3 X3 + ... + Wim Xm + ViUi 
C)  Xi = Wi1 F1 + Wi2 F2 + Wi3 F3 + ... + Wim Fm + ViUi 
D)  Xi = Ai1 F1 + Ai2 F2 + Ai3 F3 + ... + Aim Fm

Question 20

The unrotated factor matrix seldom results in factors that can be interpreted because the factors are correlated with many variables.

Accepted Answer

A) True 
 B)False

Exam 19: Factor Analysis

A is a lower triangle matrix showing the simple correlations, r, between all possible pairs of variables included in the analysis.

The factors identified in factor analysis are overtly observed in the population.

Factor analysis is somewhat similar to discriminant analysis in that each variable is expressed as a linear combination of underlying factors.

A _ is a plot of the original variables using the factor loadings as coordinates.

Which of the following applications is appropriate for using factor analysis?

Which statement is not true about principal components analysis (PCA)?

A factor model that provides a good fit to the data has many large residuals.

The various methods of factor analysis are differentiated by the approach used to derive the weights or factor score coefficients.

Which is not a method of factor analysis?

It is recommended that the factors extracted should account for at least of the variance.

It is possible to compute as many principal components as there are variables; in doing so, parsimony is gained.

Factor loadings represent the correlations between sets of variables.

Bartlett's test of sphericity is one test of the appropriateness of the factor model.

When selecting surrogate variables from variables with similarly high loadings, the choice should be based on _ .

Generally, the number of factors determined by a scree plot will be one or a few less than that determined by the eigenvalue criterion.

What are the steps involved in conducting factor analysis (Figure 19.3 in the text)?

Communality is .

Which method of analysis does not classify variables as dependent or independent?

If the variables are standardized, the factor model may be presented as .

The unrotated factor matrix seldom results in factors that can be interpreted because the factors are correlated with many variables.

Introduction to Marketing

Defining the Marketing Research

Research Design

Exploratory Research Design

Exploratory Research Design

Descriptive Research Design

Causal Research Design

Measurement and Scaling

Measurement and Scaling

Questionnaire and Form

Sampling: Design and

Sampling: Final and Initial

Fieldwork

Data Preparation

Frequency Distribution, Crosstabulation, and Hypothesis

Analysis of Variance and

Correlation and Regression

Discriminant and Logit

Cluster Analysis

Multidimensional Scaling and

Structural Equation Modeling

Report Preparation and

International Marketing

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