Vos, Paul and Holbert, Don (2021) Frequentist Statistical Inference without Repeated Sampling. [Preprint]
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Abstract
Frequentist inference typically is described in terms of hypothetical repeated sampling but there are advantages to an interpretation that uses a single random sample.
Contemporary examples are given that indicate probabilities for random phenomena are interpreted as classical probabilities, and this interpretation of equally likely
chance outcomes is applied to statistical inference using urn models. These are used
to address Bayesian criticisms of frequentist methods. Recent descriptions of p-values,
confidence intervals, and power are viewed through the lens of classical probability
based on a single random sample from the population.
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Item Type: | Preprint | |||||||||
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Additional Information: | Accepted (Dec 2021) for publication in Synthese. | |||||||||
Keywords: | classical probability, equally likely outcomes, statistical ensemble, multiset, p-value, confidence interval | |||||||||
Subjects: | General Issues > Philosophers of Science Specific Sciences > Probability/Statistics |
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Depositing User: | Paul Vos | |||||||||
Date Deposited: | 27 Dec 2021 23:54 | |||||||||
Last Modified: | 27 Dec 2021 23:54 | |||||||||
Item ID: | 20046 | |||||||||
Subjects: | General Issues > Philosophers of Science Specific Sciences > Probability/Statistics |
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Date: | 9 December 2021 | |||||||||
URI: | https://philsci-archive.pitt.edu/id/eprint/20046 |
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