Error and the Growth of Experimental Knowledge

University of Chicago (1996)
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Abstract

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.

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Deborah Mayo
Virginia Tech

Citations of this work

Representation and Invariance of Scientific Structures.Patrick Suppes - 2002 - CSLI Publications (distributed by Chicago University Press).
Type I error rates are not usually inflated.Mark Rubin - 2024 - Journal of Trial and Error 4 (2):46-71.
Robustness Analysis as Explanatory Reasoning.Jonah N. Schupbach - 2018 - British Journal for the Philosophy of Science 69 (1):275-300.

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