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Frequentist Statistical Inference without Repeated Sampling

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
Creators:
CreatorsEmailORCID
Vos, Paulvosp@ecu.edu0000-0001-9996-5627
Holbert, Donholbertd@ecu.edu
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
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
Date: 9 December 2021
URI: http://philsci-archive.pitt.edu/id/eprint/20046

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