The Concept Of Probability In Statistical Physics

Author: Y. M. Guttmann
Editor: Cambridge University Press
ISBN: 9780521621281
Size: 20,43 MB
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A most systematic study of how to interpret probabilistic assertions in the context of statistical mechanics.

Creating Modern Probability

Author: Jan von Plato
Editor: Cambridge University Press
ISBN: 9780521597357
Size: 10,10 MB
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In this book the author charts the history and development of modern probability theory.

Probabilistic Causality

Author: Ellery Eells
Editor: Cambridge University Press
ISBN: 9780521392440
Size: 14,57 MB
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In this important first book in the series Cambridge Studies in Probability, Induction and Decision Theory, Ellery Eells explores and refines current philosophical conceptions of probabilistic causality. In a probabilistic theory of causation, causes increase the probability of their effects rather than necessitate their effects in the ways traditional deterministic theories have specified. Philosophical interest in this subject arises from attempts to understand population sciences as well as indeterminism in physics. Taking into account issues involving spurious correlation, probabilistic causal interaction, disjunctive causal factors, and temporal ideas, Professor Eells advances the analysis of what it is for one factor to be a positive causal factor for another. A salient feature of the book is a new theory of token level probabilistic causation in which the evolution of the probability of a later event from an earlier event is central.

Rethinking The Foundations Of Statistics

Author: Joseph B. Kadane
Editor: Cambridge University Press
ISBN: 9780521649759
Size: 15,64 MB
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This important collection of essays is a synthesis of foundational studies in Bayesian decision theory and statistics. An overarching topic of the collection is understanding how the norms for Bayesian decision making should apply in settings with more than one rational decision maker and then tracing out some of the consequences of this turn for Bayesian statistics. There are four principal themes to the collection: cooperative, non-sequential decisions; the representation and measurement of 'partially ordered' preferences; non-cooperative, sequential decisions; and pooling rules and Bayesian dynamics for sets of probabilities. The volume will be particularly valuable to philosophers concerned with decision theory, probability, and statistics, statisticians, mathematicians, and economists.

Philosophical Lectures On Probability

Author: Bruno de Finetti
Editor: Springer Science & Business Media
ISBN: 1402082010
Size: 15,24 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.

The Foundations Of Causal Decision Theory

Author: James M. Joyce
Editor: Cambridge University Press
ISBN: 9780521641647
Size: 10,57 MB
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The early chapters of the book introduce the nonspecialist to the rudiments of expected utility theory.

Interpreting Probability

Author: David Howie
Editor: Cambridge University Press
ISBN: 9781139434379
Size: 12,43 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
Editor: Cambridge University Press
ISBN: 9781139430418
Size: 12,62 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.

Probability Theory

Author: E. T. Jaynes
Editor: Cambridge University Press
ISBN: 1139435167
Size: 18,67 MB
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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.

The Design Inference

Author: William A. Dembski
Editor: Cambridge University Press
ISBN: 1139936298
Size: 16,58 MB
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The design inference uncovers intelligent causes by isolating their key trademark: specified events of small probability. Just about anything that happens is highly improbable, but when a highly improbable event is also specified (i.e. conforms to an independently given pattern) undirected natural causes lose their explanatory power. Design inferences can be found in a range of scientific pursuits from forensic science to research into the origins of life to the search for extraterrestrial intelligence. This challenging and provocative 1998 book shows how incomplete undirected causes are for science and breathes new life into classical design arguments. It will be read with particular interest by philosophers of science and religion, other philosophers concerned with epistemology and logic, probability and complexity theorists, and statisticians.