Foundations of Probability Theory, Statistical Inference, and Statistical Theories of Science | Volume I Foundations and Philosophy of Epistemic Applications of Probability Theory

W. L. Harper (u. a.)

ISBN 10: 9027706166 / ISBN 13: 9789027706164

Published by Springer, 1975

About this Item

Foundations of Probability Theory, Statistical Inference, and Statistical Theories of Science | Volume I Foundations and Philosophy of Epistemic Applications of Probability Theory | W. L. Harper (u. a.) | Buch | xi | Englisch | Springer | EAN 9789027706164 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

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Bibliographic Details

• Title: Foundations of Probability Theory, Statistical Inference, and Statistical Theories of Science | Volume I Foundations and Philosophy of Epistemic Applications of Probability Theory
• Publisher: Springer
• Publication Date: 1975
• Language: English
• ISBN 10: 9027706166
• ISBN 13: 9789027706164
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 23D millimeters 241 millimeters width by 160 millimeters height by 23 millimeters depth
• Weight: 655 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

In May of 1973 we organized an international research colloquium on foundations of probability, statistics, and statistical theories of science at the University of Western Ontario. During the past four decades there have been striking formal advances in our understanding of logic, semantics and algebraic structure in probabilistic and statistical theories. These advances, which include the development of the relations between semantics and metamathematics, between logics and algebras and the algebraic-geometrical foundations of statistical theories (especially in the sciences), have led to striking new insights into the formal and conceptual structure of probability and statistical theory and their scientific applications in the form of scientific theory. The foundations of statistics are in a state of profound conflict. Fisher's objections to some aspects of Neyman-Pearson statistics have long been well known. More recently the emergence of Baysian statistics as a radical alternative to standard views has made the conflict especially acute. In recent years the response of many practising statisticians to the conflict has been an eclectic approach to statistical inference. Many good statisticians have developed a kind of wisdom which enables them to know which problems are most appropriately handled by each of the methods available. The search for principles which would explain why each of the methods works where it does and fails where it does offers a fruitful approach to the controversy over foundations.