ABSTRACT
Cluster analysis encompasses many diverse techniques for discovering structure within complex bodies of data. In a typical situation, one has a sample of data units (e.g., psychiatric patients) each described by scores on selected variables, such as achievement test scores. The objective is to group either the data units or the variables into clusters such that the elements within a cluster have a high degree of ‘natural association’ among themselves while the clusters are ‘relatively distinct’ from one another. The approach to the problem and the results achieved depend principally on how the investigator chooses to give operational meaning to the phrases ‘natural association’ and ‘relatively distinct’.
