The Relation of Principal Component Analysis to the Analysis of Variance

Summary Both the analysis of variance and principal component analysis divide sums of squares into orthogonal components. The major difference is that the first uses external criteria, the second internal. The calculations involved in these techniques are demonstrated with an example. The way in which data may be standardized before principal component analysis is discussed. In some cases, the information discarded on standardization may be examined by an analysis of variance, and related to the results of the principal component analysis.