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  1. The logic of tests of significance.Stephen Spielman - 1974 - Philosophy of Science 41 (3):211-226.
    In spite of the fact that the Neyman-Pearson theory of testing is the official theory of statistical testing, most research publications in the social sciences use a pattern of inductive reasoning that is characteristic of Fisherian tests of significance. The exact structure and rationale of this pattern of reasoning is widely misunderstood. The goal of the paper is to describe precisely the pattern and its rationale, and to show that while it is far more cogent than Fisher's critics have realized, (...)
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  • On Neyman's paradox and the theory of statistical tests.M. L. G. Redhead - 1974 - British Journal for the Philosophy of Science 25 (3):265-271.
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  • Logical versus historical theories of confirmation.Alan Musgrave - 1974 - British Journal for the Philosophy of Science 25 (1):1-23.
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  • A falsifying rule for probability statements.Donald A. Gillies - 1971 - British Journal for the Philosophy of Science 22 (3):231-261.
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  • (2 other versions)Error and the Growth of Experimental Knowledge.Deborah Mayo - 1997 - British Journal for the Philosophy of Science 48 (3):455-459.
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  • Bayes and Bust: Simplicity as a Problem for a Probabilist’s Approach to Confirmation. [REVIEW]Malcolm R. Forster - 1995 - British Journal for the Philosophy of Science 46 (3):399-424.
    The central problem with Bayesian philosophy of science is that it cannot take account of the relevance of simplicity and unification to confirmation, induction, and scientific inference. The standard Bayesian folklore about factoring simplicity into the priors, and convergence theorems as a way of grounding their objectivity are some of the myths that Earman's book does not address adequately. 1Review of John Earman: Bayes or Bust?, Cambridge, MA. MIT Press, 1992, £33.75cloth.
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  • Error and the Growth of Experimental Knowledge.Deborah G. Mayo - 1996 - University of Chicago.
    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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  • (2 other versions)Error and the growth of experimental knowledge.Deborah Mayo - 1996 - International Studies in the Philosophy of Science 15 (1):455-459.
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