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Bibframe Work

Title
Bayesian philosophy of science : variations on a theme by the Reverend Thomas Bayes
Type
Text
Contribution
Sprenger, Jan, (Author)
Hartmann, Stephan, 1968- (Author)
Subject
Science--Philosophy (LCSH)
Bayesian statistical decision theory (LCSH)
Bayes, Thomas, -1761
Bayes, Thomas, -1761
Bayesian statistical decision theory. (FAST)
Science--Philosophy. (FAST)
Bayes, Thomas, -1761
Science--Philosophy. (NLI)
Bayesian statistical decision theory. (NLI)
Language
English
Illustrative Content
Illustrations
Classification
DDC: 519.542 full
DDC: 501 full
LCC: QA279.5 .S68 2019
Summary
How should we reason in science? Jan Sprenger and Stephan Hartmann offer a refreshing take on classical topics in philosophy of science, using a single key concept to explain and to elucidate manifold aspects of scientific reasoning. They present good arguments and good inferences as being characterized by their effect on our rational degrees of belief. Refuting the view that there is no place for subjective attitudes in 'objective science', Sprenger and Hartmann explain the value of convincing evidence in terms of a cycle of variations on the theme of representing rational degrees of belief by means of subjective probabilities (and changing them by Bayesian conditionalization). In doing so, they integrate Bayesian inference-the leading theory of rationality in0social science-with the practice of 21st century science. Bayesian Philosophy of Science thereby shows how modeling such attitudes improves our understanding of causes, explanations, confirming evidence, and scientific models in general. It combines a scientifically minded and mathematically sophisticated approach with conceptual analysis and attention to methodological problems of modern science, especially in statistical inference, and is therefore a valuable resource for philosophers and scientific practitioners.-- Source other than the Library of Congress.
Authorized Access Point
Sprenger, Jan, Bayesian philosophy of science : variations on a theme by the Reverend Thomas Bayes