Authors
Pawel Kawalec
Katolicki Uniwersytet Lubelski (KUL)
Adam P. Kubiak
Warsaw University of Technology
Abstract
We analyse the issue of using prior information in frequentist statistical inference. For that purpose, we scrutinise different kinds of sampling designs in Jerzy Neyman’s theory to reveal a variety of ways to explicitly and objectively engage with prior information. Further, we turn to the debate on sampling paradigms to argue that Neyman’s theory supports an argument for the intermediate approach in the frequentism vs. Bayesianism debate. We also demonstrate that Neyman’s theory, by allowing non-epistemic values to influence evidence collection and formulation of statistical conclusions, does not compromise the epistemic reliability of the procedures and may improve it. This undermines the value-free ideal of scientific inference.
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DOI 10.1007/s10838-022-09600-x
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References found in this work BETA

Science, Policy, and the Value-Free Ideal.Heather Douglas - 2009 - University of Pittsburgh Press.
Logic of Statistical Inference.Ian Hacking - 1965 - Cambridge, England: Cambridge University Press.
In Defence of the Value Free Ideal.Gregor Betz - 2013 - European Journal for Philosophy of Science 3 (2):207-220.

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