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NCJ Number: 249592 Find in a Library
Title: Use of Likelihood Ratios for Evidence Quantification in Forensic Applications - Recorded Seminar at the NIJ 2015 Impression, Pattern and Trace Evidence Symposium
Author(s): Hari Iyer
Date Published: August 2015
Page Count: 2
Sponsoring Agency: Forensic Technology Center of Excellence (FTCoE)
Research Triangle Park, NC 27709-2194
Sale Source: Forensic Technology Center of Excellence (FTCoE)
c/o RTI International
3040 Cornwallis Road
Research Triangle Park, NC 27709-2194
United States of America
Document: HTML (Registration Required)
Type: Instructional Material (Programmed); Technical Assistance
Format: Document; Document (Online); Web Page/Site
Language: English
Country: United States of America
Annotation: This online registration page for the “On-Demand” course entitled “Use of Likelihood Ratios for Evidence Quantification in Forensic Applications” presents a course description, course accreditation, recommended audience, and background information on the presenter.
Abstract: This course is sponsored by the National Institute of Justice’s (NIJ’s) Forensic Technology Center of Excellence. It was originally presented at the 2015 Impression, Pattern and Trace Evidence Symposium (IPTES) under the section for Forensic Sciences, Forensic Technology, Impression Pattern Evidence, and Law Enforcement Training. The course is recommended for forensic practitioners. It addresses issues that have arisen as a result of growing support for the use of a Likelihood Ratio (more properly referred to as Bayes Factor) as a measure of the strength of a forensic determination that evidence found at a crime scene is linked to a particular suspect. It is not widely known, however, that there are fundamental flaws associated with viewing the Bayes Factor as a measure of the strength of the Forensic examiner’s determination that a particular piece of crime-scene evidence is linked to a particular suspect. The course will explain these flaws in the use of the Bayes Factor and provide illustrative examples that explain the corresponding consequences of relying on the Bayes Factor. Alternative approaches for quantifying the strength of forensic match determinations are offered in the course. The presenter is Hari lyer of the Statistical Engineering Division of the National Institute of Standards and Technology’s Information Technology Laboratory.
Main Term(s): Forensic science training
Index Term(s): Computer aided instruction; Evidence identification; Mathematical modeling; NIJ grant-related documents; NIJ Resources; Probabilistic evidence
To cite this abstract, use the following link:
http://www.ncjrs.gov/App/publications/abstract.aspx?ID=271738

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