Causation, Prediction and Search (Lecture Notes in Statistics, #81) (Adaptive Computation and Machine Learning)

by Peter Spirtes, etc., C. Glymour, and R. Scheines

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Book cover for Causation, Prediction and Search

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This book is intended for anyone, regardless of discipline, who is interested in the use of statistical methods to help obtain scientific explanations or to predict the outcomes of actions, experiments or policies. Much of G. Udny Yule's work illustrates a vision of statistics whose goal is to investigate when and how causal influences may be reliably inferred, and their comparative strengths estimated, from statistical samples. Yule's enterprise has been largely replaced by Ronald Fisher's conception, in which there is a fundamental cleavage between experimental and non- experimental inquiry, and statistics is largely unable to aid in causal inference without randomized experimental trials. Every now and then members of the statistical community express misgivings about this turn of events, and, in our view, rightly so. Our work represents a return to something like Yule's conception of the enterprise of theoretical statistics and its potential practical benefits. If intellectual history in the 20th century had gone otherwise, there might have been a discipline to which our work belongs. As it happens, there is not.
We develop material that belongs to statistics, to computer science, and to philosophy; the combination may not be entirely satisfactory for specialists in any of these subjects. We hope it is nonetheless satisfactory for its purpose.
  • ISBN10 3540979794
  • ISBN13 9783540979791
  • Publish Date March 1993 (first published 24 February 1993)
  • Publish Status Out of Print
  • Out of Print 14 March 1996
  • Publish Country DE
  • Publisher Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
  • Imprint Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Format Paperback (UK Trade)
  • Pages 549
  • Language English