11 – Cluster Analysis

Publisher Summary This chapter provides an overview of the uses of cluster methods and describes the procedures involved in conducting cluster analyses. Cluster analysis is a term used to describe a family of statistical procedures specifically designed to discover classifications within complex data sets. The objective of cluster analysis is to group objects into clusters such that objects within one cluster share more in common with one another than they do with the objects of other clusters. Thus, the purpose of the analysis is to arrange objects into relatively homogeneous groups based on multivariate observations. Furthermore, the chapter discusses the uses for cluster analysis. Clustering methods are useful whenever the researcher is interested in grouping together objects based on multivariate similarity. Cluster analysis can be employed as a data exploration tool as well as a hypothesis testing and confirmation tool. The most frequent use of cluster analysis is in the development of a typology or classification system. However, cluster analysis is not a single standardized procedure, and there are pitfalls associated with its improper use, therefore, care is required in its application.

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