Error and the Growth of Experimental Knowledge

목차

Deborah G. Mayo, Error and the Growth of Experimental Knowledge (Chicago and London: The University of Chicago Press, 1996).

1. Learning from Error
2. Ducks, Rabbits, and Normal Sciences: Recasting the Kuhn's Eye View of Popper
3. The New Experimentalism and the Bayesian Way
4. Duhem, Kuhn, and Bayes
5. Models of Experimental Inquiry
6. Severe Tests and Methodological Underdetermination
7. The Experimental Basis from Which to Test Hypotheses: Brownian Motion
8. Severe Tests and Novel Evidence
9. Hunting and Snooping: Understanding the Neyman-Pearson Predesignationist Stance
10. Why You Cannot Be Just a Little Bit Bayesian
11. Why Pearson Rejected the Neyman-Pearson (Behavioristic) Philosophy and a Note on Objectivity in Statistics
12. Error Statistics and Peircean Error Correction
13. Toward an Error-Statistical Philosophy of Science