An introduction to the practical application of cluster analysis, this text presents a selection of methods which together can deal with most applications. These methods are chosen for their robustness, consistency and general applicability. Discusses the main approaches to clustering and provides guidance in choosing between the available methods. Also discusses various types of data, including interval-scaled and binary variables as well as similarity data and explains how these can be transformed prior to clustering. Contains numerous exercises.