Multivariate Data Analysis Chapter 9 - Cluster Analysis

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# Multivariate Data Analysis Chapter 9 - Cluster Analysis - PowerPoint PPT Presentation

Multivariate Data Analysis Chapter 9 - Cluster Analysis. MIS 6093 Statistical Method Instructor: Dr. Ahmad Syamil. 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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### Multivariate Data AnalysisChapter 9 - Cluster Analysis

MIS 6093 Statistical Method

Chapter 9
• What Is Cluster Analysis?
• How Does Cluster Analysis Work?
• Measuring Similarity
• Forming Clusters
• Determining the Number of Clusters in the Final Solution
Chapter 9Cluster Analysis Decision Process
• Stage One: Objectives of Cluster Analysis
• Selection of Clustering Variables
Chapter 9Cluster Analysis Decision Process Cont.
• 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
Chapter 9Cluster Analysis Decision Process Cont.
• Stage 3: Assumptions in Cluster Analysis
• Representativeness of the Sample
• Impact of Multicollinearity
Chapter 9Cluster Analysis Decision Process Cont.
• Stage 4: Deriving Clusters and Assessing Overall Fit
• Clustering Algorithms
• Hierarchical Cluster Procedures
• 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
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
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
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
Chapter 9
• Summary
• Questions

……end