The Mind's Arrows: Bayes Nets and Graphical Causal Models in Psychology

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Overview

In recent years, small groups of statisticians, computer scientists, and philosophers have developed an account of how partial causal knowledge can be used to compute the effect of actions and how causal relations can be learned, at least by computers. The representations used in the emerging theory are causal Bayes nets or graphical causal models.

In his new book, Clark Glymour provides an informal introduction to the basic assumptions, algorithms, and techniques of causal Bayes nets and graphical causal models in the context of psychological examples. He demonstrates their potential as a powerful tool for guiding experimental inquiry and for interpreting results in developmental psychology, cognitive neuropsychology, psychometrics,
social psychology, and studies of adult judgment. Using Bayes net techniques, Glymour suggests novel experiments to distinguish among theories of human causal learning and reanalyzes various experimental results that have been interpreted or misinterpreted -- without the benefit of Bayes nets and graphical causal models. The capstone illustration is an analysis of the methods used in
Herrnstein and Murray's book The Bell Curve; Glymour argues that new, more reliable methods of data analysis, based on Bayes nets representations, would lead to very different conclusions from those advocated by Herrnstein and Murray.

The MIT Press

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Product Details

  • ISBN-13: 9780262072205
  • Publisher: MIT Press
  • Publication date: 5/7/2004
  • Series: Bradford Books Series
  • Edition description: New Edition
  • Pages: 240
  • Sales rank: 1,091,021
  • Product dimensions: 6.00 (w) x 9.00 (h) x 1.00 (d)

Meet the Author

Clark Glymour is Senior Research Scientist at IHMC and Alumni University Professor of
Philosophy at Carnegie Mellon University.
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Table of Contents

Acknowledgments
1 Introduction 1
I Development Psychology and Discovery 5
2 Android Epistemology for Babies 7
3 Another Way for Nerds to Make Babies: The Frame Problem and Causal Inference in Development Psychology 19
II Adult Judgements of Causation 49
4 A Puzzling Experiment 51
5 The Puzzle Resolved 63
6 Marilyn vos Savant Meets Rescorla and Wagner 69
7 Cheng Models 75
8 Learning Procedures 93
9 Representation and Rationality: The Case of Backward Blocking 103
III Inference and Explanation in Cognitive Neuropsychology 111
10 Cognitive Parts: From Freud to Farah 113
11 Inferences to Cognitive Architecture from Individual Case Studies 129
12 Group Data in Cognitive Neuropsychology 151
13 The Explanatory Power of Lesioning Neural Nets 159
IV Psychometrics and Social Psychology 169
14 Social Statistics and Genuine Inquiry: The Case of The Bell Curve 171
Notes 205
References 209
Index 219
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