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- catalog abstract "Improving Statistical Reasoning presents new studies of how people think and act on probabilistic information, focusing on the details of how statistical reasoning works and on training programs that can exploit people's natural cognitive capabilities to improve their statistical reasoning. Training programs that take into account findings from evolutionary psychology and instructional theory are shown to have substantially larger effects that are more stable over time than previous training regimens. The theoretical implications of the work are presented in a neural network model of human performance on statistical reasoning problems. This book will be of interest to scholars in the fields of judgment and decision making and cognitive science, and to teachers of statistics and probabilistic reasoning.".
- catalog contributor b12076816.
- catalog created "c1999.".
- catalog date "1999".
- catalog date "c1999.".
- catalog dateCopyrighted "c1999.".
- catalog description "1. Statistical Reasoning: How Good Are We? -- 2. Are People Condemned to Remain Poor Probabilists? -- 3. Prior Training Studies -- 4. What Makes Statistical Training Effective? -- 5. Conjunctive-Probability Training -- 6. Conditional-Probability Training -- 7. Bayesian-Inference Training I -- 8. Bayesian-Inference Training II -- 9. Sample-Size Training I -- 10. A Flexible Urn Model -- 11. Sample-Size Training II -- 12. Implications of Training Results -- 13. Associationist Models of Statistical Reasoning: Architectures and Constraints -- 14. The PASS Model -- 15. Statistical Reasoning: A New Perspective -- App. A. Variations of Bayesian Inference -- App. B. The Law of Large Numbers and Sample-Size Tasks.".
- catalog description "Improving Statistical Reasoning presents new studies of how people think and act on probabilistic information, focusing on the details of how statistical reasoning works and on training programs that can exploit people's natural cognitive capabilities to improve their statistical reasoning. Training programs that take into account findings from evolutionary psychology and instructional theory are shown to have substantially larger effects that are more stable over time than previous training regimens. The theoretical implications of the work are presented in a neural network model of human performance on statistical reasoning problems.".
- catalog description "Includes bibliographical references (p. 216-229) and indexes.".
- catalog description "This book will be of interest to scholars in the fields of judgment and decision making and cognitive science, and to teachers of statistics and probabilistic reasoning.".
- catalog extent "x, 238 p. :".
- catalog identifier "0805832823 (hc : alk. paper)".
- catalog issued "1999".
- catalog issued "c1999.".
- catalog language "eng".
- catalog publisher "Mahwah, N.J. ; London : Lawrence Erlbaum Associates,".
- catalog subject "519.5 21".
- catalog subject "Mathematical statistics.".
- catalog subject "QA276.12 .S424 1999".
- catalog tableOfContents "1. Statistical Reasoning: How Good Are We? -- 2. Are People Condemned to Remain Poor Probabilists? -- 3. Prior Training Studies -- 4. What Makes Statistical Training Effective? -- 5. Conjunctive-Probability Training -- 6. Conditional-Probability Training -- 7. Bayesian-Inference Training I -- 8. Bayesian-Inference Training II -- 9. Sample-Size Training I -- 10. A Flexible Urn Model -- 11. Sample-Size Training II -- 12. Implications of Training Results -- 13. Associationist Models of Statistical Reasoning: Architectures and Constraints -- 14. The PASS Model -- 15. Statistical Reasoning: A New Perspective -- App. A. Variations of Bayesian Inference -- App. B. The Law of Large Numbers and Sample-Size Tasks.".
- catalog title "Improving statistical reasoning : theoretical models and practical implications / Peter Sedlmeier.".
- catalog type "text".