Question 1

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

Question 2

________ is a class of procedures primarily used for data reduction and summarization.

Accepted Answer

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

Question 3

If interpreting factors using the rotated factor matrix, a negative coefficient for a negative variable (prevention of tooth decay is not important)would lead to a positive interpretation (prevention of tooth decay is important).

Accepted Answer

A) True 
 B)False

Question 4

Under what general circumstances is factor analysis used?

Accepted Answer

Factor analysis is used in the following

Question 5

Factor analysis examines the whole set of interdependent relationships among variables.

Accepted Answer

A) True 
 B)False

Question 6

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 7

A factor is an underlying dimension that explains the correlations among a set of variables.

Accepted Answer

A) True 
 B)False

Question 8

Which of the following is a way to interpret factors?

Accepted Answer

A) based on the variables that load high on a factor 
B) by plotting the variables using the factor loadings as coordinates 
C) both A and B 
D) none of the above 
A) based on the variables that load high on a factor 
B) by plotting the variables using the factor loadings as coordinates 
C) both A and B 
D) none of the above

Question 9

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

Question 10

The equation Xi = Ai1 F1 + Ai2 F2 + Ai3 F3 + ...+ Aim Fm + ViUi , represents the common factors expressed as linear combinations of the observed variables.

Accepted Answer

A) True 
 B)False

Question 11

Factor loadings represent the correlations between sets of variables.

Accepted Answer

A) True 
 B)False

Question 12

The test statistic for sphericity is based on a chi-square transformation of the determinant of the correlation matrix. A large value of the test statistic will favor the acceptance of the null hypothesis.

Accepted Answer

A) True 
 B)False

Question 13

The first step in conducting factor analysis is ________.

Accepted Answer

A) construct the correlation matrix 
B) determine the method of factor analysis 
C) formulate the problem 
D) determine the number of factors 
A) construct the correlation matrix 
B) determine the method of factor analysis 
C) formulate the problem 
D) determine the number of factors

Question 14

________ should be used when factors in the population are likely to be strongly correlated.

Accepted Answer

A) Orthogonal rotation 
B) The varimax procedure 
C) Oblique rotation 
D) None of the above 
A) Orthogonal rotation 
B) The varimax procedure 
C) Oblique rotation 
D) None of the above

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

Principal components analysis is appropriate when the primary concern is to identify the underlying dimensions and the common variance is of interest.

Accepted Answer

A) True 
 B)False

Question 17

The percentage of the total variance attributed to each factor analysis model is called the percentage of variance.

Accepted Answer

A) True 
 B)False

Question 18

Factor analysis is a(n)________ in that the entire set of interdependent relationships is examined.

Accepted Answer

A) KMO measure of sampling adequacy 
B) orthogonal procedure 
C) interdependence technique 
D) varimax procedure 
A) KMO measure of sampling adequacy 
B) orthogonal procedure 
C) interdependence technique 
D) varimax procedure

Question 19

Discuss the process of selecting surrogate variables. Also discuss how the researcher should decide on which variable to choose in complex situations.

Accepted Answer

Selection of substitute, or surrogate va

Question 20

Which statement is not correct concerning factor scores?

Accepted Answer

A) In principal components analysis it is possible to compute exact factor scores that are uncorrelated. 
B) In common factor analysis, estimates of factor scores are obtained, and there is no guarantee that factors will be uncorrelated with each other. 
C) Factor scores can be used instead of the original variables in subsequent multivariate analysis. 
D) All statements are correct. 
A) In principal components analysis it is possible to compute exact factor scores that are uncorrelated. 
B) In common factor analysis, estimates of factor scores are obtained, and there is no guarantee that factors will be uncorrelated with each other. 
C) Factor scores can be used instead of the original variables in subsequent multivariate analysis. 
D) All statements are correct.

Exam 19: Factor Analysis

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

________ is a class of procedures primarily used for data reduction and summarization.

If interpreting factors using the rotated factor matrix, a negative coefficient for a negative variable (prevention of tooth decay is not important)would lead to a positive interpretation (prevention of tooth decay is important).

Under what general circumstances is factor analysis used?

Factor analysis examines the whole set of interdependent relationships among variables.

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

A factor is an underlying dimension that explains the correlations among a set of variables.

Which of the following is a way to interpret factors?

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

The equation Xi = Ai1 F1 + Ai2 F2 + Ai3 F3 + ...+ Aim Fm + ViUi , represents the common factors expressed as linear combinations of the observed variables.

Factor loadings represent the correlations between sets of variables.

The test statistic for sphericity is based on a chi-square transformation of the determinant of the correlation matrix. A large value of the test statistic will favor the acceptance of the null hypothesis.

The first step in conducting factor analysis is ________.

________ should be used when factors in the population are likely to be strongly correlated.

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

Principal components analysis is appropriate when the primary concern is to identify the underlying dimensions and the common variance is of interest.

The percentage of the total variance attributed to each factor analysis model is called the percentage of variance.

Factor analysis is a(n)________ in that the entire set of interdependent relationships is examined.

Discuss the process of selecting surrogate variables. Also discuss how the researcher should decide on which variable to choose in complex situations.

Which statement is not correct concerning factor scores?

Introduction to Marketing Research

Defining the Marketing Research Problem and Developing an Approach

Research Design

Exploratory Research Design: Secondary Data

Exploratory Research Design: Qualitative Research

Descriptive Research Design: Survey and Observation

Causal Research Design: Experimentation

Measurement and Scaling: Fundamentals and Comparative Scaling

Measurement and Scaling: Noncomparative Scaling Techniques

Questionnaire and Form Design

Sampling: Design and Procedures

Sampling: Final and Initial Sample Size Determination

Fieldwork

Data Preparation

Frequency Distribution, Cross-Tabulation, and Hypothesis Testing

Analysis of Variance and Covariance

Correlation and Regression

Discriminant and Logit Analysis

Cluster Analysis

Multidimensional Scaling and Conjoint Analysis

Structural Equation Modeling and Path Analysis

Report Preparation and Presentation

International Marketing Research

Filters

The equation X_i= A_i1 F₁+ A_i2 F₂₊A_i3 F₃+ ...+ A_im F_{m +}V_iU_i, represents the common factors expressed as linear combinations of the observed variables.