David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Synthese 90 (2):233 - 262 (1992)
I document some of the main evidence showing that E. S. Pearson rejected the key features of the behavioral-decision philosophy that became associated with the Neyman-Pearson Theory of statistics (NPT). I argue that NPT principles arose not out of behavioral aims, where the concern is solely with behaving correctly sufficiently often in some long run, but out of the epistemological aim of learning about causes of experimental results (e.g., distinguishing genuine from spurious effects). The view Pearson did hold gives a deeper understanding of NPT tests than their typical formulation as accept-reject routines, against which criticisms of NPT are really directed. The Pearsonian view that emerges suggests how NPT tests may avoid these criticisms while still retaining what is central to these methods: the control of error probabilities.
|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
Isaac Levi (1980). The Enterprise of Knowledge: An Essay on Knowledge, Credal Probability, and Chance. The MIT Press.
Ian Hacking (1976). Logic of Statistical Inference. Cambridge University Press.
A. W. F. Edwards (1972). Likelihood. Cambridge [Eng.]University Press.
Citations of this work BETA
Greg Gandenberger (2015). A New Proof of the Likelihood Principle. British Journal for the Philosophy of Science 66 (3):475-503.
Kent Staley (2012). Strategies for Securing Evidence Through Model Criticism. European Journal for Philosophy of Science 2 (1):21-43.
Philip Mirowski (1994). A Visible Hand in the Marketplace of Ideas: Precision Measurement as Arbitage. Science in Context 7 (3).
Philip Mirowski (1995). Civilization and Its Discounts. Dialogue 34 (03):541-.
Similar books and articles
Spencer Graves (1978). On the Neyman-Pearson Theory of Testing. British Journal for the Philosophy of Science 29 (1):1-23.
Andrés Rivadulla (1991). Mathematical Statistics and Metastatistical Analysis. Erkenntnis 34 (2):211 - 236.
Peter Godfrey-Smith (1994). Of Nulls and Norms. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1994:280 - 290.
Deborah G. Mayo (1983). An Objective Theory of Statistical Testing. Synthese 57 (3):297 - 340.
Johannes Lenhard (2006). Models and Statistical Inference: The Controversy Between Fisher and Neyman–Pearson. British Journal for the Philosophy of Science 57 (1):69-91.
Deborah G. Mayo (1991). Novel Evidence and Severe Tests. Philosophy of Science 58 (4):523-552.
Deborah G. Mayo & Aris Spanos (2006). Severe Testing as a Basic Concept in a Neyman–Pearson Philosophy of Induction. British Journal for the Philosophy of Science 57 (2):323-357.
Lester E. Krueger (1998). The Ego has Landed! The .05 Level of Statistical Significance is Soft (Fisher) Rather Than Hard (Neyman/Pearson). Behavioral and Brain Sciences 21 (2):207-208.
Deborah G. Mayo (1985). Behavioristic, Evidentialist, and Learning Models of Statistical Testing. Philosophy of Science 52 (4):493-516.
Deborah G. Mayo (1982). On After-Trial Criticisms of Neyman-Pearson Theory of Statistics. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1982:145 - 158.
Added to index2009-01-28
Total downloads76 ( #39,928 of 1,724,889 )
Recent downloads (6 months)5 ( #134,552 of 1,724,889 )
How can I increase my downloads?