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Belief, Evidence, and UncertaintyError-Statistics, Evidence, and Severity

Belief, Evidence, and Uncertainty: Error-Statistics, Evidence, and Severity [Several non-Bayesian and non-Likelihood accounts of evidence have been worked out in interesting detail. One such account has been championed by the philosopher Deborah Mayo and the statistician Ari Spanos. Following Popper, it assumes from the outset that to test a hypothesis is to submit it to a severe test. Unlike Popper it relies on the notion of error frequencies central to Neyman-Pearson statistics. Unlike Popper as well, Mayo and Spanos think that global theories like Newtonian mechanics are tested in a piecemeal way, by submitting their component hypotheses to severe tests. We argue that the error-statistical notion of severity is not adequately “severe,” that the emphasis on piecemeal testing procedures is misplaced, and that the Mayo-Spanos account of evidence is mistakenly committed to a “true model” assumption. In a technical Appendix we deflect Mayo’s critique of the multiple-model character of our account of evidence.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Belief, Evidence, and UncertaintyError-Statistics, Evidence, and Severity

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/lp/springer-journals/belief-evidence-and-uncertainty-error-statistics-evidence-and-severity-zAnt4riLXm
Publisher
Springer International Publishing
Copyright
© The Author(s) 2016
ISBN
978-3-319-27770-7
Pages
73 –91
DOI
10.1007/978-3-319-27772-1_6
Publisher site
See Chapter on Publisher Site

Abstract

[Several non-Bayesian and non-Likelihood accounts of evidence have been worked out in interesting detail. One such account has been championed by the philosopher Deborah Mayo and the statistician Ari Spanos. Following Popper, it assumes from the outset that to test a hypothesis is to submit it to a severe test. Unlike Popper it relies on the notion of error frequencies central to Neyman-Pearson statistics. Unlike Popper as well, Mayo and Spanos think that global theories like Newtonian mechanics are tested in a piecemeal way, by submitting their component hypotheses to severe tests. We argue that the error-statistical notion of severity is not adequately “severe,” that the emphasis on piecemeal testing procedures is misplaced, and that the Mayo-Spanos account of evidence is mistakenly committed to a “true model” assumption. In a technical Appendix we deflect Mayo’s critique of the multiple-model character of our account of evidence.]

Published: Mar 5, 2016

Keywords: Error-statistics; Severe tests; Error-probabilities; Piecemeal testing; Global theories; The “true-model” assumption; Multiple models

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