Preface --; 1 The data --; Discussion --; 2 Univariate plots and descriptive statistics --; Discussion --; 3 Scatterplot, correlation and covariance --; Discussion --; 4 Face plots --; Discussion --; 5 Multiple linear regression --; 5.1 Introductory remarks --; 5.2 The model of multiple linear regression --; 5.3 Least squares estimation --; 5.4 Residual analysis --; 5.5 Model building, analysis of variance --; 5.6 The overall test of significance --; 5.7 Coefficient of determination and multiple correlation --; 5.8 Tests of partial hypotheses --; 5.9 Standard errors of the regression coefficients --; 5.10 Selection of a subset of regressors --; Discussion --; Further study --; 6 Linear combinations --; 6.1 Introduction --; 6.2 A special linear combination --; 6.3 Linear combinations of two variables --; 6.4 Linear combinations of several variables --; 6.5 Mean and standard deviation of linear combinations --; 7 Linear discriminant analysis for two groups --; 7.1 Introduction --; 7.2 Multivariate standard distance --; 7.3 Relationship between discriminant analysis and multiple linear regression --; 7.4 Testing hypotheses about the discriminant function --; 7.5 Screening a discriminant function --; 7.6 Further uses of the coefficient of determination --; 7.7 Classification of observations --; 8 Identification analysis --; 8.1 Introduction --; 8.2 Identification analysis as a special case of discriminant analysis --; 8.3 More about standard distance --; 8.4 Identification of a bank note --; 8.5 Analysis of outliers --; 9 Specification analysis --; 9.1 Standard distance between a sample and a hypothetical mean vector --; 9.2 Specification analysis of the bank notes --; 9.3 Confidence regions for a mean vector --; 9.4 A more general model --; 9.5 Specification faces --; 10 Principal component analysis --; 10.1 Introduction --; 10.2 Principal components of two variables --; 10.3 Properties of principal components in the multidimensional case --; 10.4 Principal component analysis of the genuine bank notes --; 10.5 The singular case --; 10.6 Principal components, standard distance, and the multivariate normal distribution --; 10.7 Standard errors of the principal component coefficients and related problems --; 10.8 Principal component analysis of several groups --; 11 Comparing the covariance structures of two groups --; 11.1 Introduction --; 11.2 The bivariate case --; 11.3 The multivariate case --; 11.4 Comparison of the covariance matrices of the genuine and forged bank notes --; 11.5 Partial statistics for the analysis of Ymaxand Ymix --; 11.6 Stepwise analysis of Ymax and Ymix --; 11.7 Relationships to standard distance and principal component analysis --; 11.8 Critical values of the distribution of Fmaxand Fmix --; 12 Exercises --; 12.1 Exercises based on the bank note data --; 12.2 Additional exercises --; 13 Mathematical appendix --; 13.1 Introduction and preliminaries --; 13.2 Data matrix, mean vector, covariance and correlation --; 13.3 Multiple linear regression --; 13.4 Linear combinations --; 13.5 Multivariate standard distance and the linear discriminant function --; 13.6 Principal component analysis --; 13.7 Comparison of two covariance matrices --; References.