David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Philosophy of Science 71 (5):1007-1025 (2004)
The growing availability of computer power and statistical software has greatly increased the ease with which practitioners apply statistical methods, but this has not been accompanied by attention to checking the assumptions on which these methods are based. At the same time, disagreements about inferences based on statistical research frequently revolve around whether the assumptions are actually met in the studies available, e.g., in psychology, ecology, biology, risk assessment. Philosophical scrutiny can help disentangle 'practical' problems of model validation, and conversely, a methodology of statistical model validation can shed light on a number of issues of interest to philosophers of science.
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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.
Kent Staley & Aaron Cobb (2011). Internalist and Externalist Aspects of Justification in Scientific Inquiry. Synthese 182 (3):475-492.
Deborah G. Mayo (2008). How to Discount Double-Counting When It Counts: Some Clarifications. British Journal for the Philosophy of Science 59 (4):857-879.
Aris Spanos (2007). Curve Fitting, the Reliability of Inductive Inference, and the Error-Statistical Approach. Philosophy of Science 74 (5):1046-1066.
Deborah G. Mayo & Aris Spanos (2006). Philosophical Scrutiny of Evidence of Risks: From Bioethics to Bioevidence. Philosophy of Science 73 (5):803-816.
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