Methods for Statistical Data Analysis of Multivariate Observations (Revised)

This expanded and updated edition integrates techniques and data-based interpretations relevant for multidata analysis. The material on cluster analysis has been extended to reflect the vigorous development of methods as well as applications in the field of pattern recognition. Contains new sections which focus on issues of inputs to clustering algorithms and on the critical need for aids in interpreting the results of cluster analysis. Describes the latest graphical techniques for assessing separations among the eigenvalues of a correlation matrix and for comparing sets of eigenvectors. Includes a new appendix on software to help with statistical computing aspects. Features scores of examples and tables.