Provides a definitive review of the state of best practice for statistical testimony across a wide range of the forensic sciences, including DNA and fingerprint matching, handwriting analysis, foot prints, eye witness identification, tool marks, bite marks, etc.
Provides a definitive review of the state of best practice for statistical testimony across a wide range of the forensic sciences, including DNA and fingerprint matching, handwriting analysis, foot prints, eye witness identification, tool marks, bite marks, etc.
David Banks is a professor in Department of Statistical Science at Duke University. He is a former coordinating editor of the Journal of the American Statistical Association, director of the Statistical and Applied Mathematical Sciences Institute, and a Fellow of the ASA and the Institute of Mathematical Statistics. Karen Kafadar is a Commonwealth Professor and the chair of the Department of Statistics at the University of Virginia. She is a former president of the ASA; a Fellow of the International Statistics Institute, the ASA and the AAAS; and a former member of the Forensic Science Standards Board (FSSB) of the Organization of Scientific Area Committees for Forensic Science (OSAC). David Kaye is Distinguished Professor of Law Emeritus at Pennsylvania State University and Regents' Professor of Law and Life Sciences Emeritus at Arizona State University. He is a former editor of Jurimetrics Journal; a member of the FSSB; and the 2020 recipient of the Association of American Law Schools' Wigmore Lifetime Achievement Award for contributions to the understanding of the proof process and the rules of evidence. Maria Tackett is an assistant professor of the practice in Department of Statistical Science at Duke University.
Inhaltsangabe
1. The history of forensic inference and statistics: a thematic perspective. 2. Frequentist methods for statistical inference. 3. Bayesian methods and forensic inference. 4. Comparing philosophies of statistical inference. 5. Decision theory. 6. Association does not imply discrimination: Clarifying when matches are (and are not) meaningful. 7. Validation of forensic automatic likelihood ratio methods. 8. Bayesian networks in forensic science. 9. How well do lay people comprehend statistical statements from forensic scientists? 10. Forensic statistics in the courtroom. 11. DNA frequencies and probabilities. 12. Kinship. 13. Statistical support for conclusions in fingerprint examinations. 14. Probabilistic considerations when interpreting data base search and selection effects. 15. Comparing handwriting in questioned documents. 16. An introduction to firearms examination for researchers in statistics. 17. Shoeprints: the path from practice to science. 18. Forensic glass evidence. 19. Estimation of insect age for assessing minimum post-mortem interval in forensic entomology casework. 20. Statistical models in forensic voice comparison. 21. Bringing new statistical approaches to eyewitness evidence.
1. The history of forensic inference and statistics: a thematic perspective. 2. Frequentist methods for statistical inference. 3. Bayesian methods and forensic inference. 4. Comparing philosophies of statistical inference. 5. Decision theory. 6. Association does not imply discrimination: Clarifying when matches are (and are not) meaningful. 7. Validation of forensic automatic likelihood ratio methods. 8. Bayesian networks in forensic science. 9. How well do lay people comprehend statistical statements from forensic scientists? 10. Forensic statistics in the courtroom. 11. DNA frequencies and probabilities. 12. Kinship. 13. Statistical support for conclusions in fingerprint examinations. 14. Probabilistic considerations when interpreting data base search and selection effects. 15. Comparing handwriting in questioned documents. 16. An introduction to firearms examination for researchers in statistics. 17. Shoeprints: the path from practice to science. 18. Forensic glass evidence. 19. Estimation of insect age for assessing minimum post-mortem interval in forensic entomology casework. 20. Statistical models in forensic voice comparison. 21. Bringing new statistical approaches to eyewitness evidence.
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