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Bayesians Versus Frequentists A Philosophical Debate on Statistical Reasoning /

This book analyzes the origins of statistical thinking as well as its related philosophical questions, such as causality, determinism or chance. Bayesian and frequentist approaches are subjected to a historical, cognitive and epistemological analysis, making it possible to not only compare the two c...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Vallverdú, Jordi (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:SpringerBriefs in Statistics,
Temas:
Acceso en línea:Texto Completo

MARC

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505 0 |a Some Questions to Begin with -- Ancient Statistics History in a Nutshell -- The Bayesian Approach and its Evolution until the Beginning of 20th Century -- A Conceptual Reply to Reverend Bayes: the Frequentist Approach -- The Co-evolution, Battles and Fights of Both Paradigms -- The Birth of Multicausality as the Death of Causality and Their Statistical Corollaries.- Natural vs. Artificial Minds and the Supercomputing Era -- And the Winner is... -- References. 
520 |a This book analyzes the origins of statistical thinking as well as its related philosophical questions, such as causality, determinism or chance. Bayesian and frequentist approaches are subjected to a historical, cognitive and epistemological analysis, making it possible to not only compare the two competing theories, but to also find a potential solution. The work pursues a naturalistic approach, proceeding from the existence of numerosity in natural environments to the existence of contemporary formulas and methodologies to heuristic pragmatism, a concept introduced in the book's final section. This monograph will be of interest to philosophers and historians of science and students in related fields. Despite the mathematical nature of the topic, no statistical background is required, making the book a valuable read for anyone interested in the history of statistics and human cognition. 
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