David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Philosophia Mathematica 15 (2):166-192 (2007)
Gillies introduced a propensity interpretation of probability which is linked to experience by a falsifying rule for probability statements. The present paper argues that general statistical tests should qualify as falsification rules. The ‘goodness-of-fit paradox’ is introduced: the confirmation of a probability model by a test refutes the model's validity. An example is given in which an independence test introduces dependence. Several possibilities to interpret the paradox and to deal with it are discussed. It is concluded that the propensity interpretation properly reflects statistical practice, but it is not as objective as some adherents claim.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
John L. Pollock (1986). The Paradox of the Preface. Philosophy of Science 53 (2):246-258.
Christopher S. I. Mccurdy (1996). Humphrey's Paradox and the Interpretation of Inverse Conditional Propensities. Synthese 108 (1):105 - 125.
Donald Gillies (2002). Causality, Propensity, and Bayesian Networks. Synthese 132 (1-2):63 - 88.
Marcel Weber (2001). Determinism, Realism, and Probability in Evolutionary Theory. Proceedings of the Philosophy of Science Association 2001 (3):S213-.
Max Albert (1992). Die Falsifikation Statistischer Hypothesen. Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 23 (1):1 - 32.
Thomas Bartelborth (2011). Propensities and Transcendental Assumptions. Erkenntnis 74 (3):363-381.
Peter Clark (2001). Statistical Mechanics and the Propensity Interpretation of Probability. In Jean Bricmont & Others (eds.), Chance in Physics: Foundations and Perspectives. Springer 271--81.
Niall Shanks (1993). Time and the Propensity Interpretation of Probability. Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 24 (2):293 - 302.
Deborah G. Mayo (1985). Behavioristic, Evidentialist, and Learning Models of Statistical Testing. Philosophy of Science 52 (4):493-516.
Donald Gillies (2000). Varieties of Propensity. British Journal for the Philosophy of Science 51 (4):807-835.
Added to index2009-01-28
Total downloads27 ( #125,141 of 1,777,882 )
Recent downloads (6 months)4 ( #143,201 of 1,777,882 )
How can I increase my downloads?