[spsp-members] Making Peace in the Statistics Wars: Simulation Studies in the Philosophy of Statistics - International Postdoc Forum for the Philosophy of Science

[Alan Love]

*13 April 2022, 12:15pm CDT (UTC+5)*
*Making Peace in the Statistics Wars: Simulation Studies in the Philosophy
of Statistics*
WJ Peden (Philosophy, Erasmus University Rotterdam)

*Abstract*: What constitutes a good statistical test? According to
frequentists, the test should follow a procedure that would minimise
inference in the long-run. According to Bayesians, the test should
discriminate among models according to a coherent structure of beliefs.
Deborah Mayo has called these debates the “Statistics Wars.” These debates
generally involve a mixture of intuition arguments, existence proofs, and
proofs about the methodologies’ long-run consequences. Unfortunately, both
frequentism and Bayesianism do well on these grounds. A different approach
is to simulate the short-run performance of “players” based on these
methodologies and their hybridisations. I discuss the results of two
collaborative research projects using this approach. We simulate a
statistical problem and compare the short-run performances of various
player settings. We obtain some surprising results, suggesting the
possibility of some peace among the “warring” factions. I consider the
philosophical implications and also propose some directions for future
research.

Commentator: Samuel Fletcher, Philosophy, University of Minnesota

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--
Alan C. Love
Winton Chair in the Liberal Arts
<https://cla.umn.edu/news-events/news/alan-love-places-evo-devo-front-and-center>
Distinguished McKnight Professor
<https://scholarswalk.umn.edu/faculty-awards/mcknight-awards/distinguished>
Department of Philosophy & Minnesota Center for Philosophy of Science
University of Minnesota
http://umn.edu/~aclove

*New Project!* Agency, Directionality, and Function: Foundations for a
Science of Purpose <https://www.biologicalpurpose.org>
*New Paper!* Reframing research on evolutionary novelty and co-option:
Character identity mechanisms versus deep homology
<https://doi.org/10.1016/j.semcdb.2022.03.030> (open access)
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