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Probability Theory: The Logic of Science (Anglais) Relié – 10 avril 2003

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Description du produit

Revue de presse

'This is not an ordinary text. It is an unabashed, hard sell of the Bayesian approach to statistics. It is wonderfully down to earth, with hundreds of telling examples. Everyone who is interested in the problems or applications of statistics should have a serious look.' SIAM News

'This book could be of interest to scientists working in areas where inference of incomplete information should be made.' Zentralblatt MATH

'… the author thinks for himself … and writes in a lively way about all sorts of things. It is worth dipping into it if only for vivid expressions of opinion. The annotated References and Bibliography are particularly good for this.' Notices of the American Mathematical Society

Présentation de l'éditeur

The standard rules of probability can be interpreted as uniquely valid principles in logic. In this book, E. T. Jaynes dispels the imaginary distinction between 'probability theory' and 'statistical inference', leaving a logical unity and simplicity, which provides greater technical power and flexibility in applications. This book goes beyond the conventional mathematics of probability theory, viewing the subject in a wider context. New results are discussed, along with applications of probability theory to a wide variety of problems in physics, mathematics, economics, chemistry and biology. It contains many exercises and problems, and is suitable for use as a textbook on graduate level courses involving data analysis. The material is aimed at readers who are already familiar with applied mathematics at an advanced undergraduate level or higher. The book will be of interest to scientists working in any area where inference from incomplete information is necessary.

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Format: Relié
Grand ponte de l'approche bayesienne, Jaynes présente dans ce livre une vision de la théorie des probabilités en tant qu'extension de la logique, depuis ses fondements jusqu'à ses applications les plus poussées. Ce livre, édité après sa mort, est en quelque sorte le "testament" de Jaynes et a illuminé ma vision des probabilités.

Tout scientifique ou étudiant voulant avoir une présentation synthétique des probabilités, des statistiques, de l'inférence, depuis l'introduction des concepts de base jusqu'à leurs applications les plus actuelles devrait lire ce livre.

Il est de plus très agréable à lire et se présente sous la forme d'un cours scindé en deux parties qui porte sur les fondamentaux puis sur les applications avancées. Il est ainsi accessible et s'avèrera extrêmement utile à tous : à l'étudiant tout comme au chercheur (ce qui est mon cas). Je me suis surpris à le dévorer, ce qui n'était pas évident étant donné son sujet et son volume. Une véritable référence.

Je renvoie le lecteur interessé à la page amazon.com de l'ouvrage sur laquelle on peut consulter la table des matières etc.
Remarque sur ce commentaire 6 personnes ont trouvé cela utile. Avez-vous trouvé ce commentaire utile ? Oui Non Commentaire en cours d'envoi...
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Commentaires client les plus utiles sur Amazon.com (beta) (Peut contenir des commentaires issus du programme Early Reviewer Rewards)

Amazon.com: 4.9 étoiles sur 5 40 commentaires
3 internautes sur 3 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 the best possible worldview 8 décembre 2016
Par Amazon Customer - Publié sur Amazon.com
Format: Format Kindle Achat vérifié
One of the most important works of the 20th century (or any century) in both philosophy and physics, Jaynes' work lays the foundation for the physical ontology and epistemology of science. This book is the completion of what amounted to a lifetime of effort on Jaynes' part, dating back to the "Mobil Lectures" where he first laid out this approach to knowledge. It follows the world of Richard Cox, who demonstrated that Bayesian probability theory naturally follows from three simple axioms that also serve to establish the connection between evidence and plausible belief.

In my opinion, this book is a required read for anyone who wishes to understand precisely how the scientific worldview is, in a mathematically defensible sense, the best possible worldview, the one that lets us optimally use evidence to develop an interlocked Bayesian network of evidence supported beliefs that can change and evolve as the evidence is accumulated. It also shows the critical connections between physics and statistical mechanics and Shannon's theorem in computational information theory, laying the foundation for a fair bit of modern physics as it demonstrates that physical entropy and information entropy are very much one and the same thing, from a certain point of view.
10 internautes sur 10 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Nice presentation of the nuances of probability 31 août 2013
Par C. Valente - Publié sur Amazon.com
Format: Relié Achat vérifié
I haven't finished reading this book yet, but the chapters I read so far gave me so much understanding of issues that are either obscure or absent in other probability and statistics books - but are of great practical importance - that I decided recommend it here.
It is true Jaynes' style is caustic against positions that are contrary to his owns. But he is very convincing on the reasons he gives to pinpoint the big holes in the so called "orthodox" school of probability and statistics.
Besides, the book is very lengthy, without being prolix, on its explanations, making it very pedagogical. Constrasting with that, nevertheless, Jaynes sometimes proposes examples that I believe only a mathematician or physicist with specific knowledge of the subject mentioned by the author will be able to follow. But those parts do not impact understanding of the main ideas.
It must be noted also that "Probaility theory: the logic of science" is mainly a theory book. Its goal is to present probability as an extension of deductive logic. It only brings a small number of exercises.
The best thing about this book, at least for me, is having a style that really makes me look forward reading the next page, something very rare for a technical book. In fact, the only other book I came across that had that virtue was the "Feynman Lectures on Physics".
2 internautes sur 2 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Bayesian statistics masterpiece 25 avril 2016
Par SDS Brooklyn - Publié sur Amazon.com
Format: Relié Achat vérifié
This is a classic - perhaps THE classic exposition of Bayesian statistics for physical scientists. Among other things, Jaynes strove to rediscover and rehabilitate Sir Harold Jeffreys, the geophysicist whose attempts to resurrect Laplacian/Bayesian statistics fell afoul of his fellow Cambridge professor, Sir Ronald Fisher, whose works (including Design of Experiments) were among the most influential of twentieth century statistics. Jaynes's own formidable achievements in adapting Bayesian statistics to physics and chemistry are legendary. There is also some amusing byplay in the form of a running critique (often confined to footnotes) of "Willy" Feller, the Princeton mathematician who authored a major textbook on probability theory.
5.0 étoiles sur 5 Really interesting book. 21 février 2017
Par zach - Publié sur Amazon.com
Format: Relié Achat vérifié
Very thought provoking and interesting look at the subject. It is the voice of common sense in a subject area where many people adhere to strict frequentist inference and the traditional examples. While covering these same topics, this book makes notes and gives counter examples. It focuses on the idea of information relative to uncertainty. The author thoroughly criticizes and is careful about assumptions and critical of them, unlike many other books/authors. Many results will end up the same as deriving them with Kolmogorov, but the approach will be different.

Note: The author writes long paragraphs describing problems and his logical approach to them. They are very important to the core understanding of his message and ideas.

I would only recommend this for graduate level work.
7 internautes sur 8 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Everyone should be Bayesian 20 mars 2016
Par W. Sturgis - Publié sur Amazon.com
Format: Relié Achat vérifié
I really think everyone should read this book, and R. T. Cox's book. This books make plain the philosophical and mathematical reasons that all statistics should be Bayesian. It only looses a star, because the book is not complete. Jaynes died before he could finish it. One of his students prepared the book for publication. I wish he had finished it while he was at it.
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