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Causation, Prediction, and Search

  • Peter Spirtes
  • Clark Glymour
  • Richard Scheines

Part of the Lecture Notes in Statistics book series (LNS, volume 81)

Table of contents

  1. Front Matter
    Pages i-xxiii
  2. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 1-24
  3. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 25-40
  4. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 41-86
  5. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 87-102
  6. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 103-162
  7. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 163-200
  8. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 201-237
  9. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 238-258
  10. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 259-305
  11. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 306-322
  12. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 323-353
  13. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 354-366
  14. Peter Spirtes, Clark Glymour, Richard Scheines
    Pages 367-480
  15. Back Matter
    Pages 481-529

About this book

Introduction

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.

Keywords

Microsoft Access Statistica algorithms boundary element method causality computation design distribution eXist knowledge probability probability distribution statistics theorem variable

Authors and affiliations

  • Peter Spirtes
    • 1
  • Clark Glymour
    • 1
  • Richard Scheines
    • 1
  1. 1.Department of PhilosophyCarnegie Mellon UniversityPittsburghUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-2748-9
  • Copyright Information Springer-Verlag New York 1993
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-7650-0
  • Online ISBN 978-1-4612-2748-9
  • Series Print ISSN 0930-0325
  • Buy this book on publisher's site
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