What is it about?
In a new paper in the European Journal for Philosophy of Science, I consider Fisher's criticism that the Neyman-Pearson approach to hypothesis testing relies on the assumption of “repeated sampling from the same population.”
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Why is it important?
This criticism is problematic for the Neyman-Pearson approach because it implies that test users need to know, for sure, what counts as the same or equivalent population as their current population. If they don't know what counts as the same or equivalent population, then they can't specify a procedure that would be able to repeatedly sample from this population, rather than from other non-equivalent populations, and without this specification Neyman-Pearson long run error rates become meaningless.
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Read the Original
This page is a summary of: “Repeated sampling from the same population?” A critique of Neyman and Pearson’s responses to Fisher, European Journal for Philosophy of Science, September 2020, Springer Science + Business Media,
DOI: 10.1007/s13194-020-00309-6.
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