Sprache: Englisch
Verlag: Crystal Dreams Publishing, 2003
ISBN 10: 0471469432 ISBN 13: 9780471469438
Anbieter: ThriftBooks-Atlanta, AUSTELL, GA, USA
Paperback. Zustand: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.
Anbieter: WeBuyBooks, Rossendale, LANCS, Vereinigtes Königreich
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In den WarenkorbZustand: Like New. Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind.
EUR 110,22
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In den WarenkorbPAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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In den WarenkorbZustand: New. pp. xi + 566.
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In den WarenkorbZustand: New. Keith E. Muller, Ph.D., is Associate Professor of Biostatistics at the University of North Carolina at Chapel Hill. He teaches classes and seminars in the theory and practice of univariate and multivariate linear models with Gaussian errors. A SAS user sinc.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 174,68
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In den WarenkorbPaperback. Zustand: Brand New. 592 pages. 10.50x8.25x1.25 inches. In Stock.
EUR 183,91
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In den WarenkorbZustand: New. This text focuses on the general linear model (GLM) theory, stated in matrix terms, which provides a more compact, clear and unified presentation of regression and ANOVA than do traditional sums of squares and scalar equations. Num Pages: 592 pages, black & white illustrations. BIC Classification: PBK; PBT; UFM. Category: (P) Professional & Vocational. Dimension: 281 x 212 x 31. Weight in Grams: 1328. . 2003. 1st Edition. Paperback. . . . . Books ship from the US and Ireland.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - The information contained in this book has served as the basis for a graduate-level biostatistics class at the University of North Carolina at Chapel Hill. The book focuses in the General Linear Model (GLM) theory, stated in matrix terms, which provides a more compact, clear, and unified presentation of regression of ANOVA than do traditional sums of squares and scalar equations.The book contains a balanced treatment of regression and ANOVA yet is very compact. Reflecting current computational practice, most sums of squares formulas and associated theory, especially in ANOVA, are not included. The text contains almost no proofs, despite the presence of a large number of basic theoretical results. Many numerical examples are provided, and include both the SAS code and equivalent mathematical representation needed to produce the outputs that are presented.All exercises involve only 'real' data, collected in the course of scientific research. The book is divided into sections covering the following topics:\* Basic Theory\* Multiple Regression\* Model Building and Evaluation\* ANOVA\* ANCOVA.