Scientific Reasoning

Peter Urbach, Colin Howson

ISBN 10: 081269578X / ISBN 13: 9780812695786

Published by Open Court Publishing Co ,U.S., US, 2006

About this Item

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".

Seller Inventory # LU-9780812695786

Bibliographic Details

• Title: Scientific Reasoning
• Publisher: Open Court Publishing Co ,U.S., US
• Publication Date: 2006
• Language: English
• ISBN 10: 081269578X
• ISBN 13: 9780812695786
• Binding: Paperback
• Edition: Third Edition.
• Condition: New
• Weight: 481 grams

About this title

Synopsis

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".