A Gentle Introduction to the Likelihood Ratio: Basic Ideas, Implementation, and Limitations

Thumbnail Image
Date
2023-08-24
Authors
Salyards, Jeff
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Authors
Person
Carriquiry, Alicia
Distinguished Professor
Research Projects
Organizational Units
Organizational Unit
Statistics

The Department of Statistics seeks to teach students in the theory and methodology of statistics and statistical analysis, preparing its students for entry-level work in business, industry, commerce, government, or academia.

History
The Department of Statistics was formed in 1948, emerging from the functions performed at the Statistics Laboratory. Originally included in the College of Sciences and Humanities, in 1971 it became co-directed with the College of Agriculture.

Dates of Existence
1948-present

Related Units

Organizational Unit
Center for Statistics and Applications in Forensic Evidence
The Center for Statistics and Applications in Forensic Evidence (CSAFE) carries out research on the scientific foundations of forensic methods, develops novel statistical methods and transfers knowledge and technological innovations to the forensic science community. We collaborate with more than 80 researchers and across six universities to drive solutions to support our forensic community partners with accessible tools, open-source databases and educational opportunities.
Journal Issue
Is Version Of
Versions
Series
Abstract
The workshop focuses on the likelihood ratio (LR) approach in forensic science. The LR, a one-number summary, quantifies how well the observations/results are explained by the prosecution's versus the defense’s propositions. While the basic idea behind the LR is simple and intuitive, challenges arise when trying to implement the approach on different types of evidence. Presenters will discuss the statistical foundations of the LR, applications in different forensic disciplines, best practices, and limitations.
Comments
This presentation is from the 107th International Association for Identification (IAI) Annual Educational Conference, National Harbor, Maryland, August 20-26, 2023. Posted with permission of CSAFE.

Copyright 2023, The Authors.
Description
Keywords
Citation
DOI
Source
Copyright