Error and the Growth of Experimental Knowledge

Preface1: Learning from Error 2: Ducks, Rabbits, and Normal Science: Recasting the Kuhn's-Eye View of Popper 3: The New Experimentalism and the Bayesian Way 4: Duhem, Kuhn, and Bayes 5: Models of Experimental Inquiry 6: Severe Tests and Methodological Underdetermination7: The Experimental Basis from Which to Test Hypotheses: Brownian Motion8: Severe Tests and Novel Evidence 9: Hunting and Snooping: Understanding the Neyman-Pearson Predesignationist Stance10: Why You Cannot Be Just a Little Bit Bayesian 11: Why Pearson Rejected the Neyman-Pearson (Behavioristic) Philosophy and a Note on Objectivity in Statistics12: Error Statistics and Peircean Error Correction 13: Toward an Error-Statistical Philosophy of Science ReferencesIndex

Summary

This text provides a critique of the subjective Bayesian view of statistical inference, and proposes the author's own error-statistical approach as an alternative framework for the epistemology of experiment. It seeks to address the needs of researchers who work with statistical analysis.

Product details

• Authors: Deborah G. Mayo
• Publisher: University Of Chicago Press
• Languages: English
• Product format: Paperback / Softback
• Released: 15.08.1996
• EAN: 9780226511986
• ISBN: 978-0-226-51198-6
• No. of pages: 509
• Dimensions: 231 mm x 154 mm x 38 mm
• Weight: 782 g
• Series: Science & Its Conceptual Found; Science & Its Conceptual Foundations S.; Science & its Conceptual Foundations Series SCF (CHUP); Science & its Conceptual Foundations Series SCF; Science and Its Conceptual Foundations series
• Subject: Natural sciences, medicine, IT, technology > Natural sciences (general)