# the concept of probability in statistical physics cambridge studies in probability induction and decision theory

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## The Concept Of Probability In Statistical Physics

**Author :**Y. M. Guttmann

**ISBN :**0521621283

**Genre :**Philosophy

**File Size :**55. 91 MB

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A most systematic study of how to interpret probabilistic assertions in the context of statistical mechanics.

## Philosophical Lectures On Probability

**Author :**Bruno de Finetti

**ISBN :**9781402082016

**Genre :**Science

**File Size :**26. 23 MB

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Bruno de Finetti (1906–1985) is the founder of the subjective interpretation of probability, together with the British philosopher Frank Plumpton Ramsey. His related notion of “exchangeability” revolutionized the statistical methodology. This book (based on a course held in 1979) explains in a language accessible also to non-mathematicians the fundamental tenets and implications of subjectivism, according to which the probability of any well specified fact F refers to the degree of belief actually held by someone, on the ground of her whole knowledge, on the truth of the assertion that F obtains.

## Interpreting Probability

**Author :**David Howie

**ISBN :**1139434373

**Genre :**Science

**File Size :**49. 5 MB

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The term probability can be used in two main senses. In the frequency interpretation it is a limiting ratio in a sequence of repeatable events. In the Bayesian view, probability is a mental construct representing uncertainty. This 2002 book is about these two types of probability and investigates how, despite being adopted by scientists and statisticians in the eighteenth and nineteenth centuries, Bayesianism was discredited as a theory of scientific inference during the 1920s and 1930s. Through the examination of a dispute between two British scientists, the author argues that a choice between the two interpretations is not forced by pure logic or the mathematics of the situation, but depends on the experiences and aims of the individuals involved. The book should be of interest to students and scientists interested in statistics and probability theories and to general readers with an interest in the history, sociology and philosophy of science.

## Decision Space

**Author :**Paul Weirich

**ISBN :**1139430416

**Genre :**Science

**File Size :**46. 78 MB

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In Decision Space: Multidimensional Utility Analysis, first published in 2001, Paul Weirich increases the power and versatility of utility analysis and in the process advances decision theory. Combining traditional and novel methods of option evaluation into one systematic method of analysis, multidimensional utility analysis is a valuable tool. It provides formulations of important decision principles, such as the principle to maximize expected utility; enriches decision theory in solving recalcitrant decision problems; and provides in particular for the cases in which an expert must make a decision for a group of people. The multiple dimensions of this analysis create a decision space broad enough to accommodate all factors affecting an option's utility. The book will be of interest to advanced students and professionals working in the subject of decision theory, as well as to economists and other social scientists.

## Creating Modern Probability

**Author :**Jan von Plato

**ISBN :**0521597358

**Genre :**Mathematics

**File Size :**34. 74 MB

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In this book the author charts the history and development of modern probability theory.

## American Book Publishing Record

**Author :**

**ISBN :**UOM:39015016313598

**Genre :**United States

**File Size :**44. 26 MB

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## Inference Method And Decision

**Author :**R.D. Rosenkrantz

**ISBN :**9789401012379

**Genre :**Science

**File Size :**44. 41 MB

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This book grew out of previously published papers of mine composed over a period of years; they have been reworked (sometimes beyond recognition) so as to form a reasonably coherent whole. Part One treats of informative inference. I argue (Chapter 2) that the traditional principle of induction in its clearest formulation (that laws are confirmed by their positive cases) is clearly false. Other formulations in terms of the 'uniformity of nature' or the 'resemblance of the future to the past' seem to me hopelessly unclear. From a Bayesian point of view, 'learning from experience' goes by conditionalization (Bayes' rule). The traditional stum bling block for Bayesians has been to fmd objective probability inputs to conditionalize upon. Subjective Bayesians allow any probability inputs that do not violate the usual axioms of probability. Many subjectivists grant that this liberality seems prodigal but own themselves unable to think of additional constraints that might plausibly be imposed. To be sure, if we could agree on the correct probabilistic representation of 'ignorance' (or absence of pertinent data), then all probabilities obtained by applying Bayes' rule to an 'informationless' prior would be objective. But familiar contra dictions, like the Bertrand paradox, are thought to vitiate all attempts to objectify 'ignorance'. BuUding on the earlier work of Sir Harold Jeffreys, E. T. Jaynes, and the more recent work ofG. E. P. Box and G. E. Tiao, I have elected to bite this bullet. In Chapter 3, I develop and defend an objectivist Bayesian approach.

## Mathematical Reviews

**Author :**

**ISBN :**UVA:X006180727

**Genre :**Mathematics

**File Size :**56. 65 MB

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## Whitaker S Books In Print

**Author :**

**ISBN :**UOM:39015043806101

**Genre :**Bibliography, National

**File Size :**89. 12 MB

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## Bpr

**Author :**

**ISBN :**STANFORD:36105111050477

**Genre :**American literature

**File Size :**22. 98 MB

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