Authors:
- Breaks new ground in building personal and scientific epistemology using the principles of belief, confirmation, and evidence
- Makes precise a distinction between the concepts of confirmation and evidence and analyzes the importance of such a distinction
- Discusses the bearings of some statistical theorems on both formal and traditional epistemologies
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Philosophy (BRIEFSPHILOSOPH)
Part of the book sub series: Philosophy of Science (BRIEFSPHILOSC)
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Table of contents (11 chapters)
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Front Matter
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Clarification, Illustration, and Defense of the Confirmation/Evidence Distinction
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Front Matter
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Comparisons with Other Philosophical Accounts of Evidence
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Front Matter
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Applications of the Confirmation/Evidence Distinction to Epistemological Puzzles
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Front Matter
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Back Matter
About this book
This book has two central aims: First, to make precise a distinction between the concepts of confirmation and evidence and to argue that failure to recognize this distinction is the source of certain otherwise intractable epistemological problems. The second goal is to demonstrate to philosophers the fundamental importance of statistical and probabilistic methods, at stake in the uncertain conditions in which for the most part we lead our lives, not simply to inferential practice in science, where they are now standard, but to epistemic inference in other contexts as well. Although the argument is rigorous, it is also accessible. No technical knowledge beyond the rudiments of probability theory, arithmetic, and algebra is presupposed, otherwise unfamiliar terms are always defined and a number of concrete examples are given. At the same time, fresh analyses are offered with a discussion of statistical and epistemic reasoning by philosophers. This book will also be of interest to scientists and statisticians looking for a larger view of their own inferential techniques.
The book concludes with a technical appendix which introduces an evidential approach to multi-model inference as an alternative to Bayesian model averaging.
Authors and Affiliations
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Montana State University, Bozeman, USA
Prasanta S. Bandyopadhyay, Gordon Brittan Jr., Mark L. Taper
About the authors
Mark L. Taper’s research involves statistical and quantitative modelling, both analytic and computational, to answer questions in conservation biology, population dynamics, conservation genetics, evolutionary ecology, community ecology, population genetics, spatial ecology, and macro ecology. He is deeply concerned with effectively connecting ecological and evolutionary theory with the real world. This has led him to work on the construction of statistical methodologies appropriate to ecological and evolutionary problems and to an interest in the epistemological foundations of both statistics and science. He co-edited with Subhash Lele, The Nature of Scientific Evidence: Scientific, Philosophical, and Empirical Considerations (University of Chicago Press, 2004).
Bibliographic Information
Book Title: Belief, Evidence, and Uncertainty
Book Subtitle: Problems of Epistemic Inference
Authors: Prasanta S. Bandyopadhyay, Gordon Brittan Jr., Mark L. Taper
Series Title: SpringerBriefs in Philosophy
DOI: https://doi.org/10.1007/978-3-319-27772-1
Publisher: Springer Cham
eBook Packages: Religion and Philosophy, Philosophy and Religion (R0)
Copyright Information: The Author(s) 2016
Softcover ISBN: 978-3-319-27770-7Published: 14 March 2016
eBook ISBN: 978-3-319-27772-1Published: 04 March 2016
Series ISSN: 2211-4548
Series E-ISSN: 2211-4556
Edition Number: 1
Number of Pages: XIII, 178
Number of Illustrations: 9 illustrations in colour
Topics: Philosophy of Science, Statistical Theory and Methods, Logic