ISBN: 9789812383563 - bayesian reasoning in data analysis: a critical introduction (4 resultados)

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Librería: HPB-Red, Dallas, TX, Estados Unidos de AmericaHPB-Red
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EUR 115,14
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hardcover. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 152,52
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Hardcover. Condición: Brand New. 329 pages. 9.00x6.00x0.75 inches. In Stock.

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Librería: moluna, Greven, Alemaniamoluna
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EUR 152,07
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Condición: New. A multi-level introduction to Bayesian reasoning. The basic ideas of this approach to the quantification of uncertainty are presented using examples from research and everyday life. Applications covered include: parametric inference combination of results.

Idioma: Inglés
Editorial: World Scientific Publishing Company Jun 2003, 2003
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 203,69
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Buch. Condición: Neu. Neuware - This book provides a multi-level introduction to Bayesian reasoning (as opposed to 'conventional statistics') and its applications to data analysis. The basic ideas of this 'new' approach to the quantification of uncertainty are presented using examples from research and everyday life. Applications covered include: parametric inference; combination of results; treatment of uncertainty due to systematic errors and background; comparison of hypotheses; unfolding of experimental distributions; upper/lower bounds in frontier-type measurements. Approximate methods for routine use are derived and are shown often to coincide -- under well-defined assumptions! -- with 'standard' methods, which can therefore be seen as special cases of the more general Bayesian methods. In dealing with uncertainty in measurements, modern metrological ideas are utilized, including the ISO classification of uncertainty into type A and type B. These are shown to fit well into the Bayesian framework.…