Numerical evaluation of cytologic data. X. Introduction to multivariate analysis of variance

Quantitative measurement on cytologic material usually involves several features for each cell. The data are thus multivariate and are represented as feature vectors. Analysis of variance on univariate data is well established for the detection of small differences between sets of data. For multivariate data, the calculating schemes are much less well known. They are presented in this paper in direct analogy to univariate procedures. The calculating schedule in a factorial design in bivariate data is demonstrated.