David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1994:280 - 290 (1994)
Neyman-Pearson methods in statistics distinguish between Type I and Type II errors. Through rigid control of Type I error, the "null" hypothesis typically receives the benefit of the doubt. I compare philosophers' interpretations of this feature of Neyman-Pearson tests with interpretations given in statistics textbooks. The pragmatic view of the tests advocated by Neyman, largely rejected by philosophers, lives on in many textbooks. Birnbaum thought the pragmatic view has a useful "heuristic" role in understanding testing. I suggest that it may have the opposite effect.
|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
Deborah G. Mayo (1992). Did Pearson Reject the Neyman-Pearson Philosophy of Statistics? Synthese 90 (2):233 - 262.
Andrés Rivadulla (1991). Mathematical Statistics and Metastatistical Analysis. Erkenntnis 34 (2):211 - 236.
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 & 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.
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.
Deborah G. Mayo (1985). Behavioristic, Evidentialist, and Learning Models of Statistical Testing. Philosophy of Science 52 (4):493-516.
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 (1991). Novel Evidence and Severe Tests. Philosophy of Science 58 (4):523-552.
G. William Moore, Grover M. Hutchins & Robert E. Miller (1986). A New Paradigm for Hypothesis Testing in Medicine, with Examination of the Neyman Pearson Condition. Theoretical Medicine and Bioethics 7 (3).
Max Albert (1992). Die Falsifikation Statistischer Hypothesen. Journal for General Philosophy of Science 23 (1):1 - 32.
David Rindskopf (1998). Null-Hypothesis Tests Are Not Completely Stupid, but Bayesian Statistics Are Better. Behavioral and Brain Sciences 21 (2):215-216.
George A. Morgan, Problems With Null Hypothesis Significance Testing (NHST): What Do the Textbooks Say?
Stephen Spielman (1974). The Logic of Tests of Significance. Philosophy of Science 41 (3):211-226.
Deborah G. Mayo (1983). An Objective Theory of Statistical Testing. Synthese 57 (3):297 - 340.
Spencer Graves (1978). On the Neyman-Pearson Theory of Testing. British Journal for the Philosophy of Science 29 (1):1-23.
Added to index2011-05-29
Total downloads10 ( #165,120 of 1,410,001 )
Recent downloads (6 months)1 ( #176,758 of 1,410,001 )
How can I increase my downloads?