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Bayesian Philosophy of Science$
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Jan Sprenger and Stephan Hartmann

Print publication date: 2019

Print ISBN-13: 9780199672110

Published to Oxford Scholarship Online: October 2019

DOI: 10.1093/oso/9780199672110.001.0001

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Theme: Bayesian Philosophy of Science

Theme: Bayesian Philosophy of Science

Chapter:
(p.1) Theme: Bayesian Philosophy of Science
Source:
Bayesian Philosophy of Science
Author(s):

Jan Sprenger

Stephan Hartmann

Publisher:
Oxford University Press
DOI:10.1093/oso/9780199672110.003.0014

This chapter sets the stage for what follows, introducing the reader to the philosophical principles and the mathematical formalism behind Bayesian inference and its scientific applications. We explain and motivate the representation of graded epistemic attitudes (“degrees of belief”) by means of specific mathematical structures: probabilities. Then we show how these attitudes are supposed to change upon learning new evidence (“Bayesian Conditionalization”), and how all this relates to theory evaluation, action and decision-making. After sketching the different varieties of Bayesian inference, we present Causal Bayesian Networks as an intuitive graphical tool for making Bayesian inference and we give an overview over the contents of the book.

Keywords:   Bayesian inference, degree of belief, probability, Dutch Book argument, probabilism, Bayesian Conditionalization, decision theory, Causal Bayesian Networks, Causal Markov condition

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