Written for advanced undergraduates and graduate students in mathematics and related disciplines, this 2005 book explains the main approaches to statistical inference, with particular emphasis on the contrasts between them. It is the first textbook to synthesize material on computational topics with basic mathematical theory. Each chapter includes instructive problems.
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G. A. Young is Professor of Statistics at Imperial College London.
R. L. Smith is Mark L. Reed Distinguished Professor of Statistics at the University of North Carolina, Chapel Hill.
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Librería: Tacoma Book Center, Tacoma, WA, Estados Unidos de America
Hardcover. Condición: Very Good. Estado de la sobrecubierta: No Dustjacket. First Edition. ISBN 0521839718. Hardback. No dustjacket. Bound in Pictorial Boards. Near Fine condition. Tight bright attractive copy with no markings to the book. As new condition. This book is Essentials of Statistical Inference (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 16). No Signature. Nº de ref. del artículo: 222814
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Librería: Plurabelle Books Ltd, Cambridge, Reino Unido
Hardcover. Condición: As New. Series: Cambridge Series in Statistical and Probabilistic Mathematics. x 225p dark green illustrated cover, pink lettering to spine, excellent copy, like new Language: English. Nº de ref. del artículo: 168639
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Librería: Antiquariat Bookfarm, Löbnitz, Alemania
Hardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 62 YOU 9780521839716 Sprache: Englisch Gewicht in Gramm: 1150. Nº de ref. del artículo: 2506021
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Librería: Better World Books Ltd, Dunfermline, Reino Unido
Condición: 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. Nº de ref. del artículo: 56686010-20
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
Condición: New. In. Nº de ref. del artículo: ria9780521839716_new
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Librería: Chiron Media, Wallingford, Reino Unido
Hardcover. Condición: New. Nº de ref. del artículo: 6666-GRD-9780521839716
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Librería: Revaluation Books, Exeter, Reino Unido
Hardcover. Condición: Brand New. 225 pages. 10.50x7.25x0.75 inches. In Stock. This item is printed on demand. Nº de ref. del artículo: __0521839718
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Condición: New. This textbook presents the concepts and results underlying the Bayesian, frequentist, and Fisherian approaches to statistical inference. Series Editor(s): Gill, R.; Ripley, Brian D.; Ross, Sheldon M.; Silverman, B.W. (St Peter's College, Oxford); Stein, M. Series: Cambridge Series in Statistical and Probabilistic Mathematics. Num Pages: 236 pages, 92 exercises. BIC Classification: PBT. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 262 x 180 x 20. Weight in Grams: 568. . 2005. Illustrated. hardcover. . . . . Nº de ref. del artículo: V9780521839716
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Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
Hardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. Nº de ref. del artículo: C9780521839716
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Librería: Rarewaves.com USA, London, LONDO, Reino Unido
Hardback. Condición: New. Aimed at advanced undergraduate and graduate students in mathematics and related disciplines, this book presents the concepts and results underlying the Bayesian, frequentist and Fisherian approaches, with particular emphasis on the contrasts between them. Computational ideas are explained, as well as basic mathematical theory. Written in a lucid and informal style, this concise text provides both basic material on the main approaches to inference, as well as more advanced material on developments in statistical theory, including: material on Bayesian computation, such as MCMC, higher-order likelihood theory, predictive inference, bootstrap methods and conditional inference. It contains numerous extended examples of the application of formal inference techniques to real data, as well as historical commentary on the development of the subject. Throughout, the text concentrates on concepts, rather than mathematical detail, while maintaining appropriate levels of formality. Each chapter ends with a set of accessible problems. Nº de ref. del artículo: LU-9780521839716
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