Introduction to Cluster Analysis

Course Content
This course introduces Cluster Analysis using SPSS. Topics covered include the selection and pre-processing of cases and variables, selecting the number of clusters and interpretation of the results - profiling and validation.  Examples include recent papers from research areas in the social sciences.  As the course proceeds, the methods introduced use more complex statistical concepts, but presentations focus on use and interpretation rather than mathematical detail.

Course Objectives

  • To introduce participants to the use of three SPSS clustering techniques
  • To understand the rationale for, the form of and the limitations of the main models
  • To learn how to choose appropriate programs, and how to choose among the various options in the programs.
  • To introduce participants to appropriate skills in interpretation of cluster methods.

Topics covered in this course include:

  • Cluster Analysis
    • Definitions
    • Research Applications
    • Illustrative Examples
    • Discipline Context
    • Choosing Between Cluster Methods
    • Theory
    • Evaluating Cluster Analysis Solutions
    • Cluster Analysis Techniques and SPSS
    • Evaluation of Clustering
  • Hierarchical Cluster Analysis
    • Distance Measures
    • Distance Measure Formulae
    • Methods
    • Examples
  • K-means
    • Notation (k-means cluster algorithms)
  • TwoStep Cluster Analysis
    • Introduction to TwoStep
    • What are the Two Steps?
    • Illustrative Example
    • TwoStep Output
    • Definitions and Procedures
    • Notation
    • TwoStep Learning Lessons
    • Making Sense of the XML File

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