Bayesian Reasoning In Data Analysis: A Critical Introduction

Giulio D'agostini

ISBN 10: 9814447951 ISBN 13: 9789814447959

Editorial: World Scientific Publishing Co Pte Ltd, 2003

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New Book. Shipped from UK. Established seller since 2000. N� de ref. del art�culo CW-9789814447959

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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.

Acerca del autor: Charlotte y Peter Fiell son dos autoridades en historia, teor�a y cr�tica del dise�o y han escrito m�s de sesenta libros sobre la materia, muchos de los cuales se han convertido en �xitos de ventas. Tambi�n han impartido conferencias y cursos como profesores invitados, han comisariado exposiciones y asesorado a fabricantes, museos, salas de subastas y grandes coleccionistas privados de todo el mundo. Los Fiell han escrito numerosos libros para TASCHEN, entre los que se incluyen 1000 Chairs, Dise�o del siglo XX, El dise�o industrial de la A a la Z, Scandinavian Design y Dise�o del siglo XXI.

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T�tulo: Bayesian Reasoning In Data Analysis: A ...
Editorial: World Scientific Publishing Co Pte Ltd
A�o de publicaci�n: 2003
Encuadernaci�n: PAP
Condici�n: New

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BAYESIAN REASONING IN DATA ANALYSIS: A CRITICAL INTRODUCTION

D'Agostini, Giulio

Publicado por World Scientific Publishing Company, 2003

ISBN 10: 9814447951 ISBN 13: 9789814447959

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Condici�n: good. This is a pre-loved book that shows moderate signs of wear from previous reading. You may notice creases, edge wear, or a cracked spine, but it remains in solid, readable condition.Please note:-May include library or rental stickers, stamps, or markings.-Supplemental materials e.g., CDs, access codes, inserts are not guaranteed.-Box sets may not come with the original outer box. If it does, the box will not be in perfect condition. -Sourced from donation centers; authenticity not verified with publisher. Your satisfaction is our top priority! If you have any questions or concerns about your order, please don't hesitate to reach out. Thank you for shopping with us and supporting small business�"happy reading! N� de ref. del art�culo: STM.2WZ

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BAYESIAN REASONING IN DATA ANALYSIS: A CRITICAL INTRODUCTION

D'Agostini, Giulio

Publicado por World Scientific Publishing Company, 2003

ISBN 10: 9814447951 ISBN 13: 9789814447959

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Bayesian Reasoning in Data Analysis : A Critical Introduction

D'Agostini, Giulio

Publicado por World Scientific Publishing Company, 2003

ISBN 10: 9814447951 ISBN 13: 9789814447959

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Bayesian Reasoning in Data Analysis : A Critical Introduction

D'Agostini, Giulio

Publicado por World Scientific Publishing Company, 2003

ISBN 10: 9814447951 ISBN 13: 9789814447959

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Bayesian Reasoning In Data Analysis: A Critical Introduction

Giulio D'agostini

Publicado por World Scientific Publishing Co Pte Ltd, SG, 2003

ISBN 10: 9814447951 ISBN 13: 9789814447959

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Paperback. Condici�n: New. Illustrated. 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. N� de ref. del art�culo: LU-9789814447959

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