Hostname: page-component-77c89778f8-vpsfw Total loading time: 0 Render date: 2024-07-20T17:55:36.405Z Has data issue: false hasContentIssue false

Comparing Probabilistic Measures of Explanatory Power

Published online by Cambridge University Press:  01 January 2022

Abstract

Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several measures of the strength of a potential explanation. These candidate measures of “explanatory power” arguably have interesting normative interpretations and consequences. What has not yet been investigated, however, is whether any of these measures are also descriptive of people's actual explanatory judgments. Here I present my own experimental work investigating this question. I argue that one measure in particular is an accurate descriptor of explanatory judgments. Then I briefly point to some implications of this result for the epistemology and the psychology of explanatory reasoning.

Type
Research Article
Copyright
Copyright © The Philosophy of Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Thanks to David Danks, John Earman, David Glass, Edouard Machery, and Jan Sprenger for helpful conversation and criticism pertaining to this research. John Earman and Edouard Machery very graciously helped to finance this project; for that, I am especially grateful. Research for this article was also supported by a grant from the Wesley Salmon Fund, offered through the University of Pittsburgh.

References

Christensen, David. 1999. “Measuring Confirmation.” Journal of Philosophy 96 (9): 437–61.CrossRefGoogle Scholar
Eells, Ellery. 1982. Rational Decision and Causality. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Good, I. J. 1960. “Weight of Evidence, Corroboration, Explanatory Power, Information and the Utility of Experiments.” Journal of the Royal Statistical Society B 22 (2): 319–31.Google Scholar
Good, I. J.. 1968. “Corroboration, Explanation, Evolving Probability, Simplicity, and a Sharpened Razor.” British Journal for the Philosophy of Science 19 (2): 123–43.CrossRefGoogle Scholar
Hartmann, Stephan, and Sprenger, Jan. 2010. “The Weight of Competence under a Realistic Loss Function.” Logic Journal of the IGPL 18 (2): 346–52.CrossRefGoogle Scholar
Kemeny, John G., and Oppenheim, Paul. 1952. “Degree of Factual Support.” Philosophy of Science 19:307–24.CrossRefGoogle Scholar
Keynes, John Maynard. 1921. A Treatise on Probability. London: Macmillan.Google Scholar
Lipton, Peter. 2001. “Is Explanation a Guide to Inference? A Reply to Wesley C. Salmon.” In Explanation: Theoretical Approaches and Applications, ed. Hon, Giora and Rakover, Sam S., 93120. Dordrecht: Kluwer.CrossRefGoogle Scholar
Lipton, Peter. 2004. Inference to the Best Explanation. 2nd ed. New York: Routledge.Google Scholar
McGrew, Timothy. 2003. “Confirmation, Heuristics, and Explanatory Reasoning.” British Journal for the Philosophy of Science 54:553–67.CrossRefGoogle Scholar
Okasha, Samir. 2000. “Van Fraassen's Critique of Inference to the Best Explanation.” Studies in History and Philosophy of Science 31 (4): 691710.CrossRefGoogle Scholar
Phillips, Lawrence D., and Edwards, Ward. 1966. “Conservatism in a Simple Probability Inference Task.” Journal of Experimental Psychology 72 (3): 346–54.CrossRefGoogle Scholar
Popper, Karl R. 1959. The Logic of Scientific Discovery. London: Hutchinson.Google Scholar
Schupbach, Jonah N. 2011. “Studies in the Logic of Explanatory Power.” PhD diss., University of Pittsburgh.CrossRefGoogle Scholar
Schupbach, Jonah N., and Sprenger, Jan. 2011. “The Logic of Explanatory Power.” Philosophy of Science 78 (1): 105–27.CrossRefGoogle Scholar
Tentori, Katya, Crupi, Vincenzo, Bonini, Nicolao, and Osherson, Daniel. 2007. “Comparison of Confirmation Measures.” Cognition 103:107–19.CrossRefGoogle ScholarPubMed