Statistical Inference As Severe Testing
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Statistical Inference as Severe Testing
Author: Deborah G. Mayo
language: en
Publisher: Cambridge University Press
Release Date: 2018-09-20
Unlock today's statistical controversies and irreproducible results by viewing statistics as probing and controlling errors.
Error and the Growth of Experimental Knowledge
Author: Deborah G. Mayo
language: en
Publisher: University of Chicago Press
Release Date: 1996-08-15
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.
Error and Inference
Author: Deborah G. Mayo
language: en
Publisher: Cambridge University Press
Release Date: 2009-10-26
Although both philosophers and scientists are interested in how to obtain reliable knowledge in the face of error, there is a gap between their perspectives that has been an obstacle to progress. By means of a series of exchanges between the editors and leaders from the philosophy of science, statistics and economics, this volume offers a cumulative introduction connecting problems of traditional philosophy of science to problems of inference in statistical and empirical modelling practice. Philosophers of science and scientific practitioners are challenged to reevaluate the assumptions of their own theories - philosophical or methodological. Practitioners may better appreciate the foundational issues around which their questions revolve and thereby become better 'applied philosophers'. Conversely, new avenues emerge for finally solving recalcitrant philosophical problems of induction, explanation and theory testing.