Skip to content

Thinking About Likelihood Ratios for Pattern Evidence

Type: Webinar
Research Area: Forensic Statistics

This CSAFE Center Wide Meeting webinar was presented by Hal Stern from University of California on January 19, 2017.

Description:
The likelihood ratio has been proposed as a logical way to summarize forensic evidence. In pattern evidence disciplines; however, the application of likelihood ratios is challenging because of the high-dimensional data involved and the lack of relevant probability models (among other issues). Score-based likelihood ratios are one approach to handling the high-dimensional data issue. The webinar reviews likelihood ratios, their role in forensic science and the potential of score-based likelihood ratios.

Related Resources

The q–q Boxplot

The q–q Boxplot

Boxplots have become an extremely popular display of distribution summaries for collections of data, especially when we need to visualize summaries for several collections simultaneously. The whiskers in the boxplot…
The Contribution of Forensic and Expert Evidence to DNA Exoneration Cases: An Interim Report

The Contribution of Forensic and Expert Evidence to DNA Exoneration Cases: An Interim Report

This report is from Simon A. Cole, Vanessa Meterko, Sarah Chu, Glinda Cooper, Jessica Weinstock Paredes, Maurice Possley, and Ken Otterbourg (2022), The Contribution of Forensic and Expert Evidence to…
Likelihood ratios for categorical count data with applications in digital forensics

Likelihood ratios for categorical count data with applications in digital forensics

We consider the forensic context in which the goal is to assess whether two sets of observed data came from the same source or from different sources. In particular, we…
CSAFE Project Update & ASCLD FRC Collaboration

CSAFE Project Update & ASCLD FRC Collaboration

This presentation highlighted CSAFE’s collaboration with the ASCLD FRC Collaboration Hub.