Question 1

A researcher concerned with outliers in the clustering model should consider which one of the following cluster algorithms?

Accepted Answer

A)  average linkage 
B)  complete linkage 
C)  single linkage 
D)  none of the above 
A)  average linkage 
B)  complete linkage 
C)  single linkage 
D)  none of the above A

Question 2

Which one of the following is true about sample size determination in cluster analysis?

Accepted Answer

A)  Appropriate sample size is reached when the observed probability is greater than alpha 
B)  Cluster analysis can be reliably applied to sample sizes as small as 10 
C)  Power analysis can be used to determine sample size 
D)  Sufficiency in generating representation of the smallest group is the most important indicator for sample size 
A)  Appropriate sample size is reached when the observed probability is greater than alpha 
B)  Cluster analysis can be reliably applied to sample sizes as small as 10 
C)  Power analysis can be used to determine sample size 
D)  Sufficiency in generating representation of the smallest group is the most important indicator for sample size D

Question 3

Which one of the following is a recommended approach for a researcher who is working with variables with disparate measurement scales?

Accepted Answer

A)  Collapse the categories to an ordinal response scale 
B)  Remove the variables that do not have common response scales 
C)  Select a different statistical procedure 
D)  Standardize the variables 
A)  Collapse the categories to an ordinal response scale 
B)  Remove the variables that do not have common response scales 
C)  Select a different statistical procedure 
D)  Standardize the variables D

Question 4

Which one of the following is NOT an optimization method?

Accepted Answer

A)  determining similarity (or dissimilarity) between units in a cluster relative to units in other clusters 
B)  examining standardized coefficients 
C)  maximizing the distance between clusters 
D)  minimizing within-clusters variation 
A)  determining similarity (or dissimilarity) between units in a cluster relative to units in other clusters 
B)  examining standardized coefficients 
C)  maximizing the distance between clusters 
D)  minimizing within-clusters variation

Question 5

Which one of the following is true about nonhierarchical clustering algorithms?

Accepted Answer

A)  The combined clusters are those that minimize the total sum of squared distance 
B)  They determine cluster similarity using the maximum or farthest distance between units in a cluster 
C)  They have small and relatively equal within-cluster variation 
D)  They minimize the within-cluster variation and maximize the between-cluster distance 
A)  The combined clusters are those that minimize the total sum of squared distance 
B)  They determine cluster similarity using the maximum or farthest distance between units in a cluster 
C)  They have small and relatively equal within-cluster variation 
D)  They minimize the within-cluster variation and maximize the between-cluster distance

Question 6

A graphical tool that can be used to assist in determining the number of factors to retain is which one of the following?

Accepted Answer

A)  Akaike's Information 
B)  dendogram 
C)  Q-Q plot 
D)  scree plot 
A)  Akaike's Information 
B)  dendogram 
C)  Q-Q plot 
D)  scree plot

Question 7

Which one of the following is the furthest neighbor algorithm selection method?

Accepted Answer

A)  average linkage 
B)  between-groups linkage 
C)  complete linkage 
D)  Ward's method 
A)  average linkage 
B)  between-groups linkage 
C)  complete linkage 
D)  Ward's method

Question 8

Which one of the following is true about the agglomeration schedule?

Accepted Answer

A)  Homogeneity of units is depicted by smaller coefficients 
B)  The coefficients in the agglomeration schedule represent the number of clusters to retain 
C)  The number of stages in the agglomeration schedule is one plus the sample size 
D)  The stopping point in the solution is indicated by small differences in coefficient values 
A)  Homogeneity of units is depicted by smaller coefficients 
B)  The coefficients in the agglomeration schedule represent the number of clusters to retain 
C)  The number of stages in the agglomeration schedule is one plus the sample size 
D)  The stopping point in the solution is indicated by small differences in coefficient values

Question 9

Which one of the following algorithms may produce inaccurate results in cases where clusters have small number of cases?

Accepted Answer

A)  average linkage 
B)  between-groups linkage 
C)  complete linkage 
D)  Ward's method 
A)  average linkage 
B)  between-groups linkage 
C)  complete linkage 
D)  Ward's method

Question 10

The starting point identified in nonhierarchical clustering algorithms is which one of the following?

Accepted Answer

A)  Chebychev distance 
B)  cluster seed 
C)  group centroid 
D)  random seed 
A)  Chebychev distance 
B)  cluster seed 
C)  group centroid 
D)  random seed

A researcher concerned with outliers in the clustering model should consider which one of the following cluster algorithms?

Which one of the following is true about sample size determination in cluster analysis?

Which one of the following is a recommended approach for a researcher who is working with variables with disparate measurement scales?

Which one of the following is NOT an optimization method?

Which one of the following is true about nonhierarchical clustering algorithms?

A graphical tool that can be used to assist in determining the number of factors to retain is which one of the following?

Which one of the following is the furthest neighbor algorithm selection method?

Which one of the following is true about the agglomeration schedule?

Which one of the following algorithms may produce inaccurate results in cases where clusters have small number of cases?

The starting point identified in nonhierarchical clustering algorithms is which one of the following?

Multivariate Statistics

Univariate and Bivariate Statistics Review

Data Screening

Multiple Linear Regression

Logistic Regression

Multivariate Analysis of Variance: Single Factor, Factorial, and Repeated Measures Designs

Discriminant Analysis

Exploratory Factor Analysis

Path Analysis, Confirmatory Factor Analysis, and Structural Equation Modeling

Multilevel Linear Modeling

Propensity Score Analysis

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Exam 8: Cluster Analysis

A researcher concerned with outliers in the clustering model should consider which one of the following cluster algorithms?

Which one of the following is true about sample size determination in cluster analysis?

Which one of the following is a recommended approach for a researcher who is working with variables with disparate measurement scales?

Which one of the following is NOT an optimization method?

Which one of the following is true about nonhierarchical clustering algorithms?

A graphical tool that can be used to assist in determining the number of factors to retain is which one of the following?

Which one of the following is the furthest neighbor algorithm selection method?

Which one of the following is true about the agglomeration schedule?

Which one of the following algorithms may produce inaccurate results in cases where clusters have small number of cases?

The starting point identified in nonhierarchical clustering algorithms is which one of the following?

Multivariate Statistics

Univariate and Bivariate Statistics Review

Data Screening

Multiple Linear Regression

Logistic Regression

Multivariate Analysis of Variance: Single Factor, Factorial, and Repeated Measures Designs

Discriminant Analysis

Exploratory Factor Analysis

Path Analysis, Confirmatory Factor Analysis, and Structural Equation Modeling

Multilevel Linear Modeling

Propensity Score Analysis

Filters