| Description |
1 online resource (xv, 222 pages) : illustrations. |
| Physical Medium |
polychrome |
| Description |
text file |
| Series |
Bradford Bks.
|
|
Bradford Bks.
|
| Note |
"A Bradford book." |
| Bibliography |
Includes bibliographical references (pages 205-217) and index. |
| Contents |
1. Introduction -- 2. Android epistemology for babies -- 3. Another way for nerds to make babies : the frame problem and causal inference in developmental psychology -- 4. A puzzling experiment -- 5. Puzzle resolved -- 6. Marilyn vos Savant meets Rescorla and Wagner -- 7. Cheng models -- 8. Learning procedures -- 9. Representation and rationality : the case of backward blocking -- 10. Cognitive parts : from Freud to Farah -- 11. Inference to cognitive architecture from individual case studies -- 12. Group data in cognitive neuropsychology -- 13. Explanatory power of lesioning neural nets -- 14. Social statistics and genuine inquiry : the case of The bell curve. |
| Summary |
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 & mdash;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. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Psychology -- Methodology.
|
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Psychology -- Methodology. |
|
Prediction theory.
|
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Prediction theory. |
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Causation.
|
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Causation. |
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Psychology -- methods. |
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Causality. |
| Genre/Form |
Electronic books.
|
| Other Form: |
Print version: Glymour, Clark N. Mind's arrows. Cambridge, Mass. : MIT Press, ©2001 0262072203 (DLC) 2001032623 (OCoLC)46908702 |
| ISBN |
9780262273961 (electronic book) |
|
0262273969 (electronic book) |
|
9780262072205 |
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0262072203 (Trade Cloth) |
|
