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Sách Causality Models, Reasoning and Inference

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Sách Causality Models, Reasoning and Inference

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Written by one of the preeminent researchers in the
field, this book provides a comprehensive exposition of modern analysis
of causation. It shows how causality has grown from a nebulous concept
into a mathematical theory with significant applications in the fields
of statistics, artificial intelligence, economics, philosophy, cognitive
science, and the health and social sciences. Judea Pearl presents and
unifies the probabilistic, manipulative, counterfactual, and structural
approaches to causation and devises simple mathematical tools for
studying the relationships between causal connections and statistical
associations. The book will open the way for including causal analysis
in the standard curricula of statistics, artificial intelligence,
business, epidemiology, social sciences, and economics. Students in
these fields will find natural models, simple inferential procedures,
and precise mathematical definitions of causal concepts that traditional
texts have evaded or made unduly complicated. The first edition of
Causality has led to a paradigmatic change in the way that causality is
treated in statistics, philosophy, computer science, social science, and
economics. Cited in more than 5,000 scientific publications, it
continues to liberate scientists from the traditional molds of
statistical thinking. In this revised edition, Judea Pearl elucidates
thorny issues, answers readers' questions, and offers a panoramic view
of recent advances in this field of research. Causality will be of
interests to students and professionals in a wide variety of fields.
Anyone who wishes to elucidate meaningful relationships from data,
predict effects of actions and policies, assess explanations of reported
events, or form theories of causal understanding and causal speech will
find this book stimulating and invaluable.
 
Categories:Mathematics
 
Year:2009
 
Edition:2nd
 
Language:english
 
Pages:484
 

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