Question 1

is a clustering procedure characterized by the development of a tree- like structure.

Accepted Answer

A)  Non- hierarchical clustering 
B)  Optimizing partitioning clustering 
C)  TwoStep clustering 
D)  Hierarchical clustering 
A)  Non- hierarchical clustering 
B)  Optimizing partitioning clustering 
C)  TwoStep clustering 
D)  Hierarchical clustering

Question 2

Cluster analysis requires prior knowledge of the cluster or group membership for each object or case included to develop the classification rule.

Accepted Answer

A) True 
 B)False

Question 3

The centroids represent the mean values of the objects contained in the cluster on each of the variables.

Accepted Answer

A) True 
 B)False

Question 4

is a procedure that first assigns or determines a cluster center and then groups all objects within a pre- specified threshold value from the center.

Accepted Answer

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

Question 5

Use of different distance measures may lead to different clustering results. Hence, it is advisable to use different measures and compare the results.

Accepted Answer

A) True 
 B)False

Question 6

Which statement is not true concerning the clustering solution if the variables are measured in vastly different units?

Accepted Answer

A)  It is desirable to eliminate outliers. 
B)  Standardization can reduce the differences between groups on variables that may best discriminate groups or clusters. 
C)  We must standardize the data by rescaling each variable to have a mean of zero and standard deviation of unity. 
D)  The clustering solution will not be influenced by the units of measurement. 
A)  It is desirable to eliminate outliers. 
B)  Standardization can reduce the differences between groups on variables that may best discriminate groups or clusters. 
C)  We must standardize the data by rescaling each variable to have a mean of zero and standard deviation of unity. 
D)  The clustering solution will not be influenced by the units of measurement.

Question 7

Why should the clustering of variables be used?

Accepted Answer

Cluster analysis is also used for cluste

Question 8

The complete linkage method of hierarchical clustering is based on the minimum distance or the nearest neighbor approach.

Accepted Answer

A) True 
 B)False

Question 9

One method of assessing reliability and validity of clustering is to use different methods of clustering and compare the results.

Accepted Answer

A) True 
 B)False

Question 10

To reduce the number of variables, a large set of variables can often be replaced by the set of cluster components.

Accepted Answer

A) True 
 B)False

Question 11

The centroid method is a variance method of hierarchical clustering in which the distance between two clusters is the distance between their centroids (means for all the variables).

Accepted Answer

A) True 
 B)False

is a clustering procedure characterized by the development of a tree- like structure.

Cluster analysis requires prior knowledge of the cluster or group membership for each object or case included to develop the classification rule.

The centroids represent the mean values of the objects contained in the cluster on each of the variables.

is a procedure that first assigns or determines a cluster center and then groups all objects within a pre- specified threshold value from the center.

Use of different distance measures may lead to different clustering results. Hence, it is advisable to use different measures and compare the results.

Which statement is not true concerning the clustering solution if the variables are measured in vastly different units?

Why should the clustering of variables be used?

The complete linkage method of hierarchical clustering is based on the minimum distance or the nearest neighbor approach.

One method of assessing reliability and validity of clustering is to use different methods of clustering and compare the results.

To reduce the number of variables, a large set of variables can often be replaced by the set of cluster components.

The centroid method is a variance method of hierarchical clustering in which the distance between two clusters is the distance between their centroids (means for all the 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

Factor Analysis

Multidimensional Scaling and

Structural Equation Modeling

Report Preparation and

International Marketing

Filters

Exam 20: Cluster Analysis

is a clustering procedure characterized by the development of a tree- like structure.

Cluster analysis requires prior knowledge of the cluster or group membership for each object or case included to develop the classification rule.

The centroids represent the mean values of the objects contained in the cluster on each of the variables.

is a procedure that first assigns or determines a cluster center and then groups all objects within a pre- specified threshold value from the center.

Use of different distance measures may lead to different clustering results. Hence, it is advisable to use different measures and compare the results.

Which statement is not true concerning the clustering solution if the variables are measured in vastly different units?

Why should the clustering of variables be used?

The complete linkage method of hierarchical clustering is based on the minimum distance or the nearest neighbor approach.

One method of assessing reliability and validity of clustering is to use different methods of clustering and compare the results.

To reduce the number of variables, a large set of variables can often be replaced by the set of cluster components.

The centroid method is a variance method of hierarchical clustering in which the distance between two clusters is the distance between their centroids (means for all the 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

Factor Analysis

Multidimensional Scaling and

Structural Equation Modeling

Report Preparation and

International Marketing

Filters