David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Philosophy of Science 77 (4):565-583 (2010)
This article calls into question the charge that frequentist testing is susceptible to the base-rate fallacy. It is argued that the apparent similarity between examples like the Harvard Medical School test and frequentist testing is highly misleading. A closer scrutiny reveals that such examples have none of the basic features of a proper frequentist test, such as legitimate data, hypotheses, test statistics, and sampling distributions. Indeed, the relevant error probabilities are replaced with the false positive/negative rates that constitute deductive calculations based on known probabilities among events. As a result, the ampliative dimension of frequentist induction—learning from data about the underlying data-generating mechanism—is missing. *Received August 2009; revised January 2010. †To contact the author, please write to: Department of Economics, Virginia Tech, Blacksburg, VA 24061; e-mail: firstname.lastname@example.org
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Citations of this work BETA
Aris Spanos (2013). Who Should Be Afraid of the Jeffreys-Lindley Paradox? Philosophy of Science 80 (1):73-93.
Aris Spanos (2013). A Frequentist Interpretation of Probability for Model-Based Inductive Inference. Synthese 190 (9):1555-1585.
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