Causality: Models, Reasoning, And Inference (First Edition, Corrected Second Printing, 2001)

Pearl, Judea

ISBN 10: 0521773628 / ISBN 13: 9780521773621

Editore: Cambridge University Press, 2001

Riguardo questo articolo

Xvi, 384 Pp. Beige Cloth Stamped In Green. First Edition, Second (Corrected) Printing, 2001. Fine In Fine Dust Jacket.

Codice articolo 046779

Dati bibliografici

• Titolo: Causality: Models, Reasoning, And Inference (First Edition, Corrected Second Printing, 2001)
• Editore: Cambridge University Press
• Data di pubblicazione: 2001
• Lingua: Inglese
• ISBN 10: 0521773628
• ISBN 13: 9780521773621
• Rilegatura: Hardcover
• Edizione: 1st Edition
• Condizione: Fine
• Condizione della sovraccoperta: Fine
• Cataloghi dei venditori:
  • Philosophy and Thoughtfulness
  • Mathematics
  • Computers and Computing

Descrizione articolo

Riassunto

Causality offers the first comprehensive coverage of causal analysis in many sciences.

Recensione

'Without assuming much beyond elementary probability theory. Judea pearl's book provides an attractive tour of recent work, in which he has played a central role, on causal models and causal reasoning. Due to his efforts, and that of a few others, a Renaissance in thinking and using causal concepts is taking place.' Patrick Suppes, Center for the Study of Language and Information, Stanford University

'Judea Pearl has come to statistics and causation with enthusiasm and creativity. his work is always thought provoking and worth careful study. This book proves to be no exception. Time and again I found myself disagreeing both with his assumptions and with his conclusions, but I was also fascinated by new insights into problems I thought I already understood well. This book illustrates the rich contributions Pearl has made to the statistical literature and to our collective understanding of models for causal reasoning.' Stephen Fienberg, Maurice Falk University professor of Statistics and Social Science, Carnegie Mellon University

'The book is extremely well written, and while mathematically precise, provides a thought-provoking study of causality and its implications.' Computing Review