Deck 20: Cluster Analysis

Question 1

The method is based on minimum distance or the nearest neighbor rule.

A) complete linkage
B) average linkage
C) single linkage
D) medium linkage

Answer 1

C

Question 2

The is a nonhierarchical method that specifies several cluster centers at once. All objects within a pre- specified threshold value from the center are grouped together.

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

Answer 2

C

Question 3

If you are performing cluster analysis on the same data using different distance measures and then comparing the results across measures to determine stability of the solutions, you are at which stage of the cluster analysis process?

A) deciding on the number of clusters
B) interpreting and profiling the clusters
C) assessing reliability and validity
D) selecting a clustering procedure

Answer 3

C

Question 4

is a class of techniques used to classify objects or cases into relatively homogeneous groups.

A) Conjoint analysis
B) Cluster analysis
C) Common factor analysis
D) Principal components analysis

Question 5

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

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

Question 6

Which of the following is not a disadvantage of nonhierarchical clustering procedures?

A) The selection of cluster centers is arbitrary.
B) The number of clusters must be pre- specified.
C) The procedures do not work well when the clusters are poorly defined.
D) All of the above are disadvantages.

Question 7

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.

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

Question 8

To use cluster analysis for clustering variables to identify homogeneous groups, the researcher could do all of the following except .

A) using the correlation coefficient as a measure of similarity between variables
B) using the variables as the units of analysis
C) inserting communalities in the diagonal of the correlation matrix
D) both A and B

Question 9

The most important part of is selecting the variables on which clustering is based.

A) formulating the clustering problem
B) selecting a clustering procedure
C) assessing the validity of clustering
D) interpreting and profiling clusters

Question 10

Cluster analysis has been used in marketing for all of the purposes below except .

A) identifying new product opportunities by clustering brands and products so that competitive sets within the market can be determined
B) determining how strongly sales are related to advertising expenditures
C) segmenting the market based on benefits sought from the purchase of a product
D) selecting test markets

Question 11

is a clustering procedure where each object starts out in a separate cluster.

A) Agglomerative clustering
B) Non- hierarchical clustering
C) Hierarchical clustering
D) Divisive clustering

Question 12

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

A) icicle plot
B) scree plot
C) cluster centers
D) both A and C

Question 13

Which of the following is a variance method of clustering?

A) Ward's method
B) complete linkage
C) optimizing partitioning
D) sequential threshold

Question 14

The method uses information on all pairs of distances, not merely the minimum or maximum distances.

A) single linkage
B) average linkage
C) complete linkage
D) medium linkage

Question 15

are agglomerative methods of hierarchical clustering in which clusters are generated to minimize the within- cluster variance.

A) Centroid methods
B) Linkage methods
C) Variance methods
D) Parallel methods

Question 16

is a clustering procedure where all objects start out in one giant cluster. Clusters are formed by dividing this cluster into smaller and smaller clusters.

A) Divisive clustering
B) Non- hierarchical clustering
C) Hierarchical clustering
D) Agglomerative clustering

Question 17

The are the initial starting points in nonhierarchical clustering.

A) cluster centers
B) factor loadings
C) factor scores
D) cluster centroids

Question 18

methods are commonly used in marketing research.

A) Agglomerative clustering
B) TwoStep clustering
C) Divisive clustering
D) Optimizing partitioning

Question 19

involves examining the cluster centroids.

A) Deciding on the number of clusters
B) Interpreting and profiling the clusters
C) Assessing reliability and validity
D) Selecting a clustering procedure

Question 20

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

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

Question 21

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 .

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

Question 22

The method is based on the maximum distance or the furthest neighbor approach.

A) complete linkage
B) medium linkage
C) single linkage
D) average linkage

Question 23

is frequently referred to as k- means clustering.

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

Question 24

Which of the following is not a procedure to check the quality of clustering results?

A) Split the data randomly into halves. Perform clustering separately on each half. Compare cluster centroids across the two subsamples.
B) Delete variables randomly. Perform clustering based on the reduced set of variables. Compare the results with those obtained by clustering based on the entire set of variables.
C) Use the same method of clustering and compare the results.
D) Perform cluster analysis on the same data using different distance measures. Compare the results across measures to determine the stability of the solutions.

Question 25

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

Question 26

Most methods are heuristics based on algorithms.

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

Question 27

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.

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

Question 28

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

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

Question 29

The most commonly used measure of similarity is the _ or its square.

A) city- block distance
B) Chebychev's distance
C) Manhattan distance
D) euclidean distance

Question 30

Which statement is not true about cluster analysis?

A) Groups or clusters are suggested by the data, not defined a priori.
B) Cluster analysis is a technique for analyzing data when the criterion or dependent variable is categorical and the independent variables are interval in nature.
C) Cluster analysis is also called classification analysis or numerical taxonomy.
D) Objects in each cluster tend to be similar to each other and dissimilar to objects in the other clusters.

Question 31

The TwoStep cluster analysis procedure can automatically determine the optimal number of clusters by comparing the values of a model- choice criteria across different clustering solutions.

Question 32

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

Question 33

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

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

Question 34

In SPSS, the main program for hierarchical clustering of objects or cases is .

A) HIERARCHICAL CLUSTER
B) FASTCLUS
C) CLUSTER ANALYSIS
D) VARCLUS

Question 35

The is a nonhierarchical method that allows for later reassignment of objects to clusters to optimize an overall criterion.

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

Question 36

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.

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

Question 37

A _ is a lower- triangle matrix containing pairwise distances between objects or cases.

A) classification matrix
B) similarity/distance coefficient matrix
C) correlation matrix
D) factor matrix

Question 38

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

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

Question 39

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

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 40

Which of the methods below is not a hierarchical method?

A) parallel threshold
B) optimizing partitioning
C) variance
D) both A and B

Question 41

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

Question 42

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

Question 43

If cluster analysis is used as a general data reduction tool, subsequent multivariate analysis can be conducted on the clusters rather than on the individual observations.

Question 44

Choice of a clustering method and choice of a distance measure are interrelated.

Question 45

It is helpful to profile the clusters in terms of variables that were not used for clustering.

Question 46

In non- hierarchical clustering, the F test is only descriptive. Because the cases or objects are systematically assigned to clusters to maximize differences on the clustering variables, the resulting probabilities should not be interpreted as testing the null hypothesis of no differences among clusters.

Question 47

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

Question 48

The primary objective of cluster analysis is to classify objects into relatively homogeneous groups.

Question 49

In the TwoStep procedure, the euclidean measure can be used only when all of the variables are ordinal.

Question 50

When cluster analysis is also used for clustering variables to identify homogeneous groups, the units used for analysis are the variables, and the distance measures are computed for all pairs of variables.

Question 51

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).

Question 52

Clustering should be done on samples of at least 300 or more.

Question 53

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

Question 54

Formal procedures for assessing the reliability and validity of clustering are simple and should be undertaken.

Question 55

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

Question 56

The parallel threshold method differs from the other two non- hierarchical clustering procedures in that the objects can later be reassigned to clusters to optimize an overall criterion.

Question 57

The dendrogram is read from right to left.

Question 58

Cluster analysis is the obverse of factor analysis in that it reduces the number of objects, not the number of variables, by grouping them into a much smaller number of clusters.

Question 59

In hierarchical clustering, the solution may depend on the order of cases in the data set.

Question 60

The average linkage method of hierarchical clustering is preferred to the single and complete linkage methods.

Question 61

What suggested guidelines researchers can use when deciding on the number of clusters?

Question 62

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

Question 63

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

Question 64

In cluster analysis, objects with larger distances between them are more similar to each other than are those at smaller distances.

Question 65

Measuring similarity in terms of distance between pairs of objects is the most common approach used in cluster analysis for grouping similar objects together.

Question 66

It is possible to obtain information on cluster membership of cases via the icicle plot if the number of clusters is specified.

Question 67

Nonhierarchical clustering is faster than hierarchical methods.

Question 68

Most clustering methods are relatively complex procedures that are supported by an extensive body of statistical reasoning.

Question 69

Cluster analysis does not classify variables as dependent or independent.

Question 70

Why should the clustering of variables be used?

Question 71

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