
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.
This book investigates how Bayesian probability theory provides a rigorous framework for understanding scientific reasoning and objective inference. Jan Sprenger and Stephan Hartmann, both established scholars in the philosophy of science, argue that scientific rationality is best understood through the lens of rational degrees of belief. By utilizing Bayesian conditionalization, the authors demonstrate that subjective probabilities are not antithetical to objective science but are instead essential tools for evaluating evidence, causality, and model selection in modern research.
What You Will Find
Experts identify this work as a significant synthesis that bridges the gap between formal statistical theory and traditional philosophical inquiry. Readers frequently note the mathematical density of the text, which serves as a foundational resource for both philosophers and active scientific practitioners.
Page Count:
416
Publication Date:
2019-10-15
Publisher:
Oxford University Press
ISBN-10:
0199672113
ISBN-13:
9780199672110
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