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
Clasificación:Libro Electrónico
Autor principal: Mayo, Deborah G.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Chicago : University of Chicago Press, 1996.
Colección:Science and its conceptual foundations.
Temas:
Bayesian statistical decision theory.
Error analysis (Mathematics)
Science > Philosophy.
Théorie de la décision bayésienne.
Théorie des erreurs.
SCIENCE / General.
Bayesian statistical decision theory
Science > Philosophy
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:
  • 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.

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