Error and the Growth of Experimental Knowledge /

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We may learn from our mistakes, but Deborah Mayo argues that, where experimental knowledge is concerned, we haven't begun to learn enough. Error and the Growth of Experimental Knowledge launches a vigorous critique of the subjective Bayesian view of statistical inference, and proposes Mayo'...

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Detalles Bibliográficos
Autor principal: Mayo, Deborah G. (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Chicago : University of Chicago Press, [1996]
Colección:Science and Its Conceptual Foundations series
Temas:
SCIENCE / General.
experimental knowledge, statistical inference, error-statistical approach, experiment, analysis, objectivity, rationality, logical inconsistencies, error, errors, mathematics, math, bayesian decision theory, science, methodological underdetermination, brownian motion, neyman-pearson predesignationist stance, peircean correction, inquiry.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Frontmatter
  • Contents
  • Preface
  • 1. Learning from Error
  • 2. Ducks, Rabbits, and Normal Science: 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
  • References
  • Index

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