Question 1

Why should the clustering of variables be used?

Accepted Answer

Cluster analysis is also used for cluste

Question 2

Which cluster analysis procedure can automatically determine the optimal number of clusters by comparing the values of a model-choice across different clustering solutions?

Accepted Answer

A) divisive 
B) sequential threshold 
C) Ward's method 
D) TwoStep 
A) divisive 
B) sequential threshold 
C) Ward's method 
D) TwoStep

Question 3

The ________ is a nonhierarchical method in which a cluster center is selected and all objects within a pre-specified threshold value from the center are grouped together.

Accepted Answer

A) optimizing partitioning method 
B) sequential threshold method 
C) parallel threshold method 
D) Ward's procedure 
A) optimizing partitioning method 
B) sequential threshold method 
C) parallel threshold method 
D) Ward's procedure

Question 4

Principal components are usually easier to interpret than the cluster components.

Accepted Answer

A) True 
 B)False

Question 5

________ is frequently referred to as k-means clustering.

Accepted Answer

A) Non-hierarchical clustering 
B) Ward's method 
C) Divisive clustering 
D) Agglomerative clustering 
A) Non-hierarchical clustering 
B) Ward's method 
C) Divisive clustering 
D) Agglomerative clustering

Question 6

In cluster analysis,the set of variables selected should describe the similarity between objects in terms that are relevant to the marketing research problem.

Accepted Answer

A) True 
 B)False

Question 7

________ is a variance method in which the squared euclidean distance to the cluster means is minimized.

Accepted Answer

A) Optimizing partitioning method 
B) Sequential threshold method 
C) Parallel threshold method 
D) Ward's procedure 
A) Optimizing partitioning method 
B) Sequential threshold method 
C) Parallel threshold method 
D) Ward's procedure

Question 8

What are the steps in conducting cluster analysis (Figure 20.3 in the text)?

Accepted Answer

The steps involved in conducting cluster

Question 9

In non-hierarchical clustering,plotting the ratio of total within-group variance to between-group variance against the number of clusters is useful if you are ________.

Accepted Answer

A) interpreting and profiling the clusters 
B) assessing the validity of clustering 
C) deciding on the number of clusters 
D) both B and C 
A) interpreting and profiling the clusters 
B) assessing the validity of clustering 
C) deciding on the number of clusters 
D) both B and C

Question 10

Which is best to use when selecting a clustering procedure: hierarchical or nonhierarchical clustering?

Accepted Answer

Although nonhierarchical clustering is f

Question 11

Which method allows the researcher to obtain information on cluster membership of cases if the number of clusters is specified?

Accepted Answer

A) factor loading plot 
B) scattergram 
C) icicle plot 
D) scree plot 
A) factor loading plot 
B) scattergram 
C) icicle plot 
D) scree plot

Question 12

Clustering should be done on samples of ________ or more.

Accepted Answer

A) 50 
B) 100 
C) 200 
D) 300 
A) 50 
B) 100 
C) 200 
D) 300

Question 13

A(n)________ or tree graph is a graphical device for displaying clustering results.Vertical lines represent clusters that are joined together.The position of the line on the scale indicates the distances at which clusters were joined.

Accepted Answer

A) dendrogram 
B) scattergram 
C) scree plot 
D) icicle diagram 
A) dendrogram 
B) scattergram 
C) scree plot 
D) icicle diagram

Why should the clustering of variables be used?

Which cluster analysis procedure can automatically determine the optimal number of clusters by comparing the values of a model-choice across different clustering solutions?

The ________ is a nonhierarchical method in which a cluster center is selected and all objects within a pre-specified threshold value from the center are grouped together.

Principal components are usually easier to interpret than the cluster components.

________ is frequently referred to as k-means clustering.

In cluster analysis,the set of variables selected should describe the similarity between objects in terms that are relevant to the marketing research problem.

________ is a variance method in which the squared euclidean distance to the cluster means is minimized.

What are the steps in conducting cluster analysis (Figure 20.3 in the text)?

In non-hierarchical clustering,plotting the ratio of total within-group variance to between-group variance against the number of clusters is useful if you are ________.

Which is best to use when selecting a clustering procedure: hierarchical or nonhierarchical clustering?

Which method allows the researcher to obtain information on cluster membership of cases if the number of clusters is specified?

Clustering should be done on samples of ________ or more.

A(n)________ or tree graph is a graphical device for displaying clustering results.Vertical lines represent clusters that are joined together.The position of the line on the scale indicates the distances at which clusters were joined.

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

Factor Analysis

Multidimensional Scaling and Conjoint Analysis

Structural Equation Modeling and Path Analysis

Report Preparation and Presentation

Filters

Exam 20: Cluster Analysis

Why should the clustering of variables be used?

Which cluster analysis procedure can automatically determine the optimal number of clusters by comparing the values of a model-choice across different clustering solutions?

The ________ is a nonhierarchical method in which a cluster center is selected and all objects within a pre-specified threshold value from the center are grouped together.

Principal components are usually easier to interpret than the cluster components.

________ is frequently referred to as k-means clustering.

In cluster analysis,the set of variables selected should describe the similarity between objects in terms that are relevant to the marketing research problem.

________ is a variance method in which the squared euclidean distance to the cluster means is minimized.

What are the steps in conducting cluster analysis (Figure 20.3 in the text)?

In non-hierarchical clustering,plotting the ratio of total within-group variance to between-group variance against the number of clusters is useful if you are ________.

Which is best to use when selecting a clustering procedure: hierarchical or nonhierarchical clustering?

Which method allows the researcher to obtain information on cluster membership of cases if the number of clusters is specified?

Clustering should be done on samples of ________ or more.

A(n)________ or tree graph is a graphical device for displaying clustering results.Vertical lines represent clusters that are joined together.The position of the line on the scale indicates the distances at which clusters were joined.

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

Factor Analysis

Multidimensional Scaling and Conjoint Analysis

Structural Equation Modeling and Path Analysis

Report Preparation and Presentation

Filters