Error and the Growth of Experimental Knowledge.

Mostrar otras versiones (1)

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'...

Descripción completa

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.

Ejemplares similares