Question 1

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

Accepted Answer

A) True 
 B)False

Question 2

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 3

________ is the last step in factor analysis.

Accepted Answer

A) Interpret the factors 
B) Determine the model fit 
C) Rotate the factors 
D) Determine the number of factors 
A) Interpret the factors 
B) Determine the model fit 
C) Rotate the factors 
D) Determine the number of factors

Question 4

The differences between the observed correlations (as given in the input correlation matrix)and the reproduced correlations (as estimated from the factor matrix)can be examined to determine model fit.

Accepted Answer

A) True 
 B)False

Question 5

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

Question 6

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

Accepted Answer

A) True 
 B)False

Question 7

Residuals are the differences between the observed correlations,as given in the input correlation matrix,and the reproduced correlations,as estimated from the factor matrix.

Accepted Answer

A) True 
 B)False

Question 8

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

Accepted Answer

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

Question 9

________ is an index that compares the magnitudes of the observed correlation coefficients to the magnitudes of the partial correlation coefficient.

Accepted Answer

A) Mahalanobis ratio 
B) KMO measure of sampling adequacy 
C) Bartlett's test of sphericity 
D) Wilks' lambda 
A) Mahalanobis ratio 
B) KMO measure of sampling adequacy 
C) Bartlett's test of sphericity 
D) Wilks' lambda

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%

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

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

________ is the last step in factor analysis.

The differences between the observed correlations (as given in the input correlation matrix)and the reproduced correlations (as estimated from the factor matrix)can be examined to determine model fit.

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

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

Residuals are the differences between the observed correlations,as given in the input correlation matrix,and the reproduced correlations,as estimated from the factor matrix.

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

________ is an index that compares the magnitudes of the observed correlation coefficients to the magnitudes of the partial correlation coefficient.

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

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

Filters

Exam 19: Factor Analysis

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

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

________ is the last step in factor analysis.

The differences between the observed correlations (as given in the input correlation matrix)and the reproduced correlations (as estimated from the factor matrix)can be examined to determine model fit.

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

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

Residuals are the differences between the observed correlations,as given in the input correlation matrix,and the reproduced correlations,as estimated from the factor matrix.

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

________ is an index that compares the magnitudes of the observed correlation coefficients to the magnitudes of the partial correlation coefficient.

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

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

Filters