ABSTRACT
This chapter reviews techniques for assessing similarity and for classifying archaeological phenomena according to their similarity. This chapter discusses the use of hierarchical cluster analysis (HCA) as a way of grouping cases based on their quantitative properties. It presents an overview of k-means clustering as way of classifying archaeological phenomena in situations where the number of classes is known a priori. Finally, this chapter outlines the use of discriminant function analysis (DFA) as a multivariate technique for classifying archaeological phenomena and it discusses ways of graphically presenting the results of DFA.
