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Synopsis
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.
Booknews
An argument for an error-statistical philosophy of science beginning with a deconstruction of the Bayesian way, Duhem, Kuhn, and countering criticisms of the Neyman-Pearson predesignationist stance. Mayo (philosophy, Virginia Polytechnic Institute) jumps right into the probability and statistics debate, changing the focus so that statistical accounts are measured according to modeling scientific inference, solving problems about evidence and inference, and performing a critique of methodological rules. She demonstrates that error-statistical account can offer a tool kit that meets these needs, and also supply a framework for making progress with the goals of new experimentalist work. Paper edition (unseen), $29.95. Annotation c. Book News, Inc., Portland, OR (booknews.com)