This graduate-level text 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. A thoroughly updated and expanded version of the authors' successful textbook on geological factor analysis, this book draws on examples from botany, zoology, ecology, and oceanography, as well as geology. Applied multivariate statistics has grown into a research area of almost unlimited potential in the natural sciences. The methods introduced in this book, such as classical principal components, principal component factor analysis, principal coordinate analysis, and correspondence analysis, can reduce masses of data to manageable and interpretable form. Q-mode and Q-R-mode methods are also presented. Special attention is given to methods of robust estimation and the identification of atypical and influential observations. Throughout the book, the emphasis is on application rather than theory.
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'Overall I found this to be an excellent volume and would certainly recommend it to anyone who wishes to understand factor analysis in the wide sense, whatever their background discipline.' David J. Hand, Journal of the Royal Statistical Society
This book explores the application of eigenanalysis to statistical data from the natural sciences. The methods introduced in this book, such as classical principal components, principal component factor analysis, and other R-mode methods of analysis, can successfully reduce masses of data to manageable and interpretable form.
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Condition: New. Explores the application of eigenanalysis to statistical data from the natural sciences to achieve statistical reduction and to construct scientific models. Num Pages: 384 pages, 67 b/w illus. BIC Classification: PBT; RB. Category: (P) Professional & Vocational. Dimension: 228 x 152 x 22. Weight in Grams: 560. . 1997. 2nd Edition. paperback. . . . . Books ship from the US and Ireland. Seller Inventory # V9780521575560
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