Preface to First Edition - lib

296 PRINCIPAL COMPONENT ANALYSISR> plot(heptathlon$score, heptathlon_pca$x[,1])heptathlon_pca$x[, 1]−4 −2 0 2 45500 6000 6500 7000heptathlon$scoreFigure 16.5Scatterplot of the score assigned to each athlete in 1988 and the firstprincipal component.ExercisesEx. 16.1 Apply principal components analysis to the covariance matrix of theheptathlon data (excluding the score variable) and compare your resultswith those given in the text, derived from the correlation matrix of thedata. Which results do you think are more appropriate for these data?Ex. 16.2 The data in Table 16.2 give measurements on five meteorologicalvariables over an 11-year period (taken from Everitt and Dunn, 2001). Thevariables areyear: the corresponding year,rainNovDec: rainfall in November and December (mm),temp: average July temperature,© 2010 by Taylor and Francis Group, LLC