An approach for deciding final clusters of a dendrogram is provided. Whether developed by agglomerative or divisive cluster analysis, decisions start at the 2-cluster level of the dendrogram. Cluster density is viewed as compactness and, therefore, is related to interindividual distances. The two clusters and the intercluster space are seen as treatments in analysis of variance with intercluster space as the control treatment. Distance in an interindividual matrix are considered measures of response to the three treatments. The F-ratio indicates if the treatment means differ; the least significant difference indicates which ones are different. The example provided expains our approach in searching for optimal clustering levels. ©1981 Kluwer Academic Publishers. Abstract reproduced with kind permission of Kluwer Academic Publishers.