Bayesian Reasoning in Data Analysis: A Critical Introduction

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9789814447959: Bayesian Reasoning in Data Analysis: A Critical Introduction

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.

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Book Description World Scientific Publishing Co Pte Ltd, Singapore, 2003. Paperback. Book Condition: New. Language: English . Brand New Book. 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. Bookseller Inventory # AAJ9789814447959

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Book Description World Scientific Publishing Co Pte Ltd, Singapore, 2003. Paperback. Book Condition: New. Language: English . Brand New Book. 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. Bookseller Inventory # AAJ9789814447959

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Book Description World Scientific Publishing Co Pte Ltd. Paperback. Book Condition: new. BRAND NEW, Bayesian Reasoning in Data Analysis: A Critical Introduction, Giulio D'Agostini, 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. Bookseller Inventory # B9789814447959

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Book Description World Scientific Publishing Company. Paperback. Book Condition: New. 352 pages. Dimensions: 9.1in. x 6.1in. x 0.9in.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; upperlower 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. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Bookseller Inventory # 9789814447959

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