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Zustand: Good. Volume 167. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9780521425339.

Zustand: Fair. Volume 167. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In fair condition, suitable as a study copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9780521425339. …

Zustand: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Paperback. Zustand: New.

Paperback. Zustand: Brand New. 232 pages. 9.25x6.25x0.75 inches. In Stock.

Paperback. Zustand: Brand New. 253 pages. 9.25x6.25x0.75 inches. In Stock.

Paperback. Zustand: New. Regression is the branch of Statistics in which a dependent variable of interest is modelled as a linear combination of one or more predictor variables, together with a random error. The subject is inherently two- or higher- dimensional, thus an understanding of Statistics in one dimension is essential.Regression: Linear Models in Statistics fills the gap between introductory statistical theory and more specialist sources of information. In doing so, it provides the reader with a number of worked examples, and exercises with full solutions.The book begins with simple linear regression (one predictor variable), and analysis of variance (ANOVA), and then further explores the area through inclusion of topics such as multiple linear regression (several predictor variables) and analysis of covariance (ANCOVA). The book concludes with special topics such as non-parametric regression and mixed models, time series, spatial processes and design of experiments.Aimed at 2nd and 3rd year undergraduates studying Statistics, Regression: Linear Models in Statistics requires a basic knowledge of (one-dimensional) Statistics, as well as Probability and standard Linear Algebra. Possible companions include John Haigh's Probability Models, and T. S. Blyth and E.F. Robertsons' Basic Linear Algebra and Further Linear Algebra.…

Zustand: Good. Light shelfwear. Inscription to the inside page. Clean and readable throughout.

Paperback. Zustand: Very Good. Zustand des Schutzumschlags: No d/j as Published. Type: Book N.B. Small plain label to inside front cover. Light rubbing to edges and corners of covers and head and tail of spine. (MATHEMATICS).

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Paperback. Zustand: Brand New. 345 pages. 8.75x5.75x1.00 inches. In Stock.

Zustand: New.

Zustand: New.

Zustand: New. pp. 300 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

Zustand: As New. Unread book in perfect condition.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Regression is the branch of Statistics in which a dependent variable of interest is modelled as a linear combination of one or more predictor variables, together with a random error. The subject is inherently two- or higher- dimensional, thus an understanding of Statistics in one dimension is essential.Regression: Linear Models in Statistics fills the gap between introductory statistical theory and more specialist sources of information. In doing so, it provides the reader with a number of worked examples, and exercises with full solutions.The book begins with simple linear regression (one predictor variable), and analysis of variance (ANOVA), and then further explores the area through inclusion of topics such as multiple linear regression (several predictor variables) and analysis of covariance (ANCOVA). The book concludes with special topics such as non-parametric regression and mixed models, time series, spatial processes and design of experiments.Aimed at 2nd and 3rd year undergraduates studying Statistics, Regression: Linear Models in Statistics requires a basic knowledge of (one-dimensional) Statistics, as well as Probability and standard Linear Algebra. Possible companions include John Haigh's Probability Models, and T. S. Blyth & E.F. Robertsons' Basic Linear Algebra and Further Linear Algebra.…

Zustand: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

hardcover. Zustand: Very Good.

Zustand: New.

Paperback. Zustand: Very Good. Same / next day dispatch (Monday - Friday).

Taschenbuch. Zustand: Neu. Regression | Linear Models in Statistics | N H Bingham (u. a.) | Taschenbuch | xiii | Englisch | 2010 | Springer London | EAN 9781848829688 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Paperback. Zustand: New.

Zustand: New.

paperback. Zustand: Gut. 546 Seiten; 9780521145770.3 Gewicht in Gramm: 1.

Paperback. Zustand: New. Regression is the branch of Statistics in which a dependent variable of interest is modelled as a linear combination of one or more predictor variables, together with a random error. The subject is inherently two- or higher- dimensional, thus an understanding of Statistics in one dimension is essential.Regression: Linear Models in Statistics fills the gap between introductory statistical theory and more specialist sources of information. In doing so, it provides the reader with a number of worked examples, and exercises with full solutions.The book begins with simple linear regression (one predictor variable), and analysis of variance (ANOVA), and then further explores the area through inclusion of topics such as multiple linear regression (several predictor variables) and analysis of covariance (ANCOVA). The book concludes with special topics such as non-parametric regression and mixed models, time series, spatial processes and design of experiments.Aimed at 2nd and 3rd year undergraduates studying Statistics, Regression: Linear Models in Statistics requires a basic knowledge of (one-dimensional) Statistics, as well as Probability and standard Linear Algebra. Possible companions include John Haigh's Probability Models, and T. S. Blyth and E.F. Robertsons' Basic Linear Algebra and Further Linear Algebra.…

Zustand: New.

Zustand: New. Leading authorities cover a wide range of currently topical problems in probability and mathematical genetics. Editor(s): Bingham, N. H.; Goldie, C. M. Series: London Mathematical Society Lecture Note Series. Num Pages: 546 pages, 30 b/w illus. 10 tables. BIC Classification: PBT; PSAK. Category: (P) Professional & Vocational. Dimension: 228 x 152 x 21. Weight in Grams: 770. . 2010. Illustrated. paperback. . . . . …