Cluster analysis of mixed-level data: Pottery provenience as an example

Provenience or “sourcing” studies of archaeological objects most commonly employ quantitative measurements of amounts of chemical constituents in the artifacts and source materials. These are then used in statistical grouping procedures known as cluster analyses. Many additional attributes of artifacts and sources, yielding lower-level qualitative data, are also of potential importance in determinations of artifact origins. These attributes are usually neglected because of the longstanding difficulty in treating “mixed-level” data, that is, combining both qualitative observations and quantitative information in a single powerful statistical procedure. A series of cluster analyses were run on two data sets consisting of archaeological pottery, using mixed-level characterization data in the CLUSTAN program with Gower's coefficient of similarity. The clustering solutions are interpretable in terms of provenience and production strategies.