Explores the application of eigenanalysis to statistical data from the natural sciences to achieve statistical reduction and to construct scientific models.Applied multivariate statistics has grown into a research area of almost unlimited potential in the natural sciences. This textbook aims to introduce students to the powerful technique of factor analysis and to provide them with the background necessary to be able to undertake analyses on their own.Applied multivariate statistics has grown into a research area of almost unlimited potential in the natural sciences. This textbook aims to introduce students to the powerful technique of factor analysis and to provide them with the background necessary to be able to undertake analyses on their own.Applied multivariate statistics has grown into a research area of almost unlimited potential in the natural sciences. The methods introduced in this book can successfully reduce masses of data to manageable and interpretable form. The authors give special attention to methods of robust estimation and the identification of atypical and influential observations. This textbook aims to introduce students of the natural sciences to the powerful technique of factor analysis and to provide them with the background necessary to be able to undertake analyses on their own. The authors explain new concepts in detail, and provide mathematical background where needed.1. Introduction; 2. Basic mathematical and statistical concepts; 3. Aims, ideas, and models of factor analysis; 4. R-Mode methods; 5. Q-Mode methods; 6. Q-R-Mode Methods; 7. Steps in the analysis; 8. Examples and case histories. ...this is an important book. Ralph D'Agostino, Journal of the American Statistical Association The second edition has been reworked to a considerable degree and contains many new references that describe advances in multivariate methods and developments since the publication of the first edition...The figures are laid out clearly and captioned.l³Ô