Behavioristic, evidentialist, and learning models of statistical testing

Philosophy of Science 52 (4):493-516 (1985)
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Abstract

While orthodox (Neyman-Pearson) statistical tests enjoy widespread use in science, the philosophical controversy over their appropriateness for obtaining scientific knowledge remains unresolved. I shall suggest an explanation and a resolution of this controversy. The source of the controversy, I argue, is that orthodox tests are typically interpreted as rules for making optimal decisions as to how to behave--where optimality is measured by the frequency of errors the test would commit in a long series of trials. Most philosophers of statistics, however, view the task of statistical methods as providing appropriate measures of the evidential-strength that data affords hypotheses. Since tests appropriate for the behavioral-decision task fail to provide measures of evidential-strength, philosophers of statistics claim the use of orthodox tests in science is misleading and unjustified. What critics of orthodox tests overlook, I argue, is that the primary function of statistical tests in science is neither to decide how to behave nor to assign measures of evidential strength to hypotheses. Rather, tests provide a tool for using incomplete data to learn about the process that generated it. This they do, I show, by providing a standard for distinguishing differences (between observed and hypothesized results) due to accidental or trivial errors from those due to systematic or substantively important discrepancies. I propose a reinterpretation of a commonly used orthodox test to make this learning model of tests explicit

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Deborah Mayo
Virginia Tech

Citations of this work

Severe testing as a basic concept in a neyman–pearson philosophy of induction.Deborah G. Mayo & Aris Spanos - 2006 - British Journal for the Philosophy of Science 57 (2):323-357.
Novel evidence and severe tests.Deborah G. Mayo - 1991 - Philosophy of Science 58 (4):523-552.
A New Proof of the Likelihood Principle.Greg Gandenberger - 2015 - British Journal for the Philosophy of Science 66 (3):475-503.

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References found in this work

Logic of Statistical Inference.Ian Hacking - 1965 - Cambridge, England: Cambridge University Press.
The Logical Foundations of Probability.Rudolf Carnap - 1950 - Journal of Philosophy 60 (13):362-364.
Logical Foundations of Probability.Ernest H. Hutten - 1950 - Journal of Symbolic Logic 16 (3):205-207.

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