Multivariate Data Analysis Chapter 9 - Cluster Analysis

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Multivariate Data AnalysisChapter 9 - Cluster
Analysis

• MIS 6093 Statistical Method
• Instructor Dr. Ahmad Syamil

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Chapter 9

• What Is Cluster Analysis?
• How Does Cluster Analysis Work?
• Measuring Similarity
• Forming Clusters
• Determining the Number of Clusters in the Final
  Solution

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Chapter 9Cluster Analysis Decision Process

• Stage One Objectives of Cluster Analysis
• Selection of Clustering Variables

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Chapter 9Cluster Analysis Decision Process Cont.

• Stage 2 Research Design in Cluster Analysis
• Detecting Outliers
• Similarity Measures
• Correlational Measures
• Distance Measures
• Comparison to Correlational Measures
• Types of Distance Measures
• Impact of Unstandardized Data Values
• Association Measures
• Standardizing the Data
• Standardizing By Variables
• Standardizing By Observation

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Chapter 9Cluster Analysis Decision Process Cont.

• Stage 3 Assumptions in Cluster Analysis
• Representativeness of the Sample
• Impact of Multicollinearity

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Chapter 9Cluster Analysis Decision Process Cont.

• Stage 4 Deriving Clusters and Assessing Overall
  Fit
• Clustering Algorithms
• Hierarchical Cluster Procedures
• Single Linkage
• Complete Linkage
• Average Linkage
• Ward's Method
• Centroid Method
• Nonhierarchical Clustering Procedures
• Sequential Threshold
• Parallel Threshold
• Optimization
• Selecting Seed Points
• Should Hierarchical or Nonhierarchical Methods Be
  Used?
• Pros and Cons of Hierarchical Methods
• Emergence of Nonhierarchical Methods
• A Combination of Both Methods
• How Many Clusters Should Be Formed?
• Should the Cluster Analysis Be Respecified

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Chapter 9Cluster Analysis Decision Process Cont.

• Stage 5 Interpretation of the Clusters
• Stage 6 Validation and Profiling of the Clusters
  
• Validating the Cluster Solution
• Profiling the Cluster Solution
• Summary of the Decision Process

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Chapter 9An Illustrative Example

• Stage 1 Objectives of the Cluster Analysis
• Stage 2 Research Design of the Cluster
• Analysis
• Stage 3 Assumptions in Cluster Analysis

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Chapter 9An Illustrative Example Cont.

• Stage 4 Deriving Clusters and Assessing
• Overall Fit
• Step 1 Hierarchical Cluster Analysis
• Step 2 Nonhierarchical Cluster Analysis
• Stage 5 Interpretation of the Clusters
• Stage 6 Validation and Profiling of the Clusters
  

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Chapter 9

• Summary
• Questions
• end