Over the past several years there has been an increasing use of the pattern recognition techniques to aid in the interpretation of large data sets. The techniques employed have generally been forms of cluster analysis. Factor analysis is a branch of multivariate analysis that has had little previous application in aiding the understanding of data sets describing natural systems. The combination of these two techniques provides a powerful tool in manipulating the data into an intelligible form. The basic principles of these statistical methods are given and their application to a set of physical and chemical analyses data of the sediments of a small lake ecosystem, Chautauqua Lake, New York, are presented.