Bayesian Philosophy of Science

Oxford and New York: Oxford University Press (2019)
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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 in social 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.



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Author Profiles

Jan Sprenger
University of Turin
Stephan Hartmann
Ludwig Maximilians Universität, München

References found in this work

Studies in the logic of explanation.Carl Gustav Hempel & Paul Oppenheim - 1948 - Philosophy of Science 15 (2):135-175.
Bayesian Epistemology.Luc Bovens & Stephan Hartmann - 2003 - Oxford: Oxford University Press. Edited by Stephan Hartmann.
Explanation and scientific understanding.Michael Friedman - 1974 - Journal of Philosophy 71 (1):5-19.
The inference to the best explanation.Gilbert H. Harman - 1965 - Philosophical Review 74 (1):88-95.
On conditionals.Dorothy Edgington - 1995 - Mind 104 (414):235-329.

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