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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 analysis chapter 9 cluster analysis

Multivariate Data AnalysisChapter 9 - Cluster Analysis

MIS 6093 Statistical Method

Instructor: Dr. Ahmad Syamil

chapter 9
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 9 cluster analysis decision process
Chapter 9Cluster Analysis Decision Process
  • Stage One: Objectives of Cluster Analysis
    • Selection of Clustering Variables
chapter 9 cluster analysis decision process cont
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
chapter 9 cluster analysis decision process cont5
Chapter 9Cluster Analysis Decision Process Cont.
  • Stage 3: Assumptions in Cluster Analysis
    • Representativeness of the Sample
    • Impact of Multicollinearity
chapter 9 cluster analysis decision process cont6
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
chapter 9 cluster analysis decision process cont7
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 9 an illustrative example
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 9 an illustrative example cont
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 910
Chapter 9
  • Summary
  • Questions

……end