Error and the growth of experimental knowledge
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.
Print Book, English, ©1996
The University of Chicago Press, Chicago, ©1996
xvi, 493 p.
9780226511979, 9780226511986, 0226511979, 0226511987
644553003
Preface 1: 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 Underdetermination 7: The Experimental Basis from Which to Test Hypotheses: Brownian Motion 8: Severe Tests and Novel Evidence 9: Hunting and Snooping: Understanding the Neyman-Pearson Predesignationist Stance 10: Why You Cannot Be Just a Little Bit Bayesian 11: Why Pearson Rejected the Neyman-Pearson (Behavioristic) Philosophy and a Note on Objectivity in Statistics 12: Error Statistics and Peircean Error Correction 13: Toward an Error-Statistical Philosophy of Science References Index
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