Error and the Growth of Experimental Knowledge

כריכה קדמית
University of Chicago Press, 15 ביולי 1996 - 493 עמודים
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We may learn from our mistakes, but Deborah Mayo argues that, where experimental knowledge is concerned, we haven't begun to learn enough. Error and the Growth of Experimental Knowledge launches a vigorous critique of the subjective Bayesian view of statistical inference, and proposes Mayo's own error-statistical approach as a more robust framework for the epistemology of experiment. Mayo genuinely addresses the needs of researchers who work with statistical analysis, and simultaneously engages the basic philosophical problems of objectivity and rationality.

Mayo has long argued for an account of learning from error that goes far beyond detecting logical inconsistencies. In this book, she presents her complete program for how we learn about the world by being "shrewd inquisitors of error, white gloves off." Her tough, practical approach will be important to philosophers, historians, and sociologists of science, and will be welcomed by researchers in the physical, biological, and social sciences whose work depends upon statistical analysis.
 

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תוכן

Learning from Error
1
Ducks Rabbits and Normal Science Recasting the KuhnsEye View of Popper
21
The New Experimentalism and the Bayesian Way
57
Duhem Kuhn and Bayes
102
Models of Experimental Inquiry
128
Severe Tests and Methodological Underdetermination
174
The Experimental Basis from Which to Test Hypotheses Brownian Motion
214
Severe Tests and Novel Evidence
251
Hunting and Snooping Understanding the NeymanPearson Predesignationist Stance
294
Why You Cannot Be Just a Little Bit Bayesian
319
Why Pearson Rejected the NeymanPearson Behavioristic Philosophy and a Note on Objectivity in Statistics
361
Error Statistics and Peircean Error Correction
412
Toward an ErrorStatistical Philosophy of Science
442
References
465
Index
481
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