Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-22T04:38:08.223Z Has data issue: false hasContentIssue false
  • English
  • Français

Prediction, Explanation, and Testability As Criteria For Judging Statistical Theories

Published online by Cambridge University Press:  14 March 2022

Brown Grier
Brown Grier*
Affiliation:
Northern Illinois University
Get access Rights & Permissions [Opens in a new window]

Abstract

For the case of statistical theories, the criteria of explanation, prediction, and testability can all be viewed as particular instances of a more general evaluation scheme. Using the ideas of a gain matrix and expected gain from statistical decision theory, these three criteria can be compared in terms of the elements in their associated gain matrices. This analysis leads to (1) further understanding of the interrelationship between the current criteria, (2) the proposal of an ordering for the criteria, and (3) the suggestion of a new criterion.

Type
Research Article
Information
Philosophy of Science , Volume 42 , Issue 4 , December 1975 , pp. 373 - 383
Copyright
Copyright © 1975 by 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.)

References

Greeno, J. G. “Evaluation of Statistical Hypothesis Using Information Transmitted.” Philosophy of Science 37 (1970): 279–294.10.1086/288301CrossRefGoogle Scholar
Salmon, W. C. Statistical Explanation and Statistical Relevance. Pittsburgh: University of Pittsburgh Press, 1971.10.2307/j.ctt6wrd9pCrossRefGoogle Scholar
Shuford, E. H., Albert, A. and Massengill, H. E. “Admissable Probability Measurement Procedures.” Psychometrica 31 (1966): 125–145.10.1007/BF02289503CrossRefGoogle Scholar