Scientific Reasoning: The Bayesian Approach

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Open Court, 2006 - Mathematics - 327 pages
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This user-friendly, comprehensive course in probability and statistics as applied to physical and social science explains the probability calculus, distributions and densities, and the rivals of Beyesianism - the classical, logical, and subjective theories. Howson and Urbach clearly lay out the theory of classical inference, the Neyman-Pearson theory of significance tests, the classical theory of estimation, and regression analysis. The work is controversial, but gives a fair and accurate account of the anti-Bayesian views it criticizes. The authors examined the way scientists actually appeal to probability arguments, and explain the 'classical' approach to statistical inference, which they demonstrate to be full of flaws. They then present the Bayesian method, showing that it avoids the difficulties of the classical system. Finally, they reply to all the major criticisms levelled against the Bayesian method, especially the charge that it is "too subjective".

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Contents

The Probability Calculus
13
The Laws of Probability
45
e The Duhem Problem
103
Copyright

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About the author (2006)

Colin Howson is Professor of Philosophy at the University of Toronto and Emeritus Professor, London School of Economics and Political Science. He is the author of Hume's Problem: Induction and the Justification of Belief (2000), Logic with Trees (1997) and, with Peter Urbach, Scientific Reasoning: The Bayesian Approach (3rd edition, 2006).

Urbach is Reader in Philosophy at the London School of Economics.

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