Statistical Issues in Assessing Forensic Evidence

Karen Kafadar

International Statistical Review, 2015, vol. 83, issue 1, 111-134

Abstract: type="main" xml:id="insr12069-abs-0001"> In 2009, the National Academy of Sciences released a report that emphasized the need for more scientific research in the evaluation of methods in the forensic science disciplines. This needed research includes statistical issues such as bias quantification, validation and estimates of accuracy and precision in different contexts. This article reviews statistical aspects of forensic science with particular reference to the design of studies that are essential to evaluate inferences from forensic evidence. Many sources can affect both the accuracy and the consistency of decisions at each stage of the process, from specimen collection to final decision. The article discusses the importance of identifying these sources and the statistical principles involved in the quantification of, and uncertainty in, estimated probabilities of error. By contrasting the design of a successful community clinical trial with two previous fingerprint studies and with bullet lead studies, this article emphasizes the need for reduced subjectivity, the types of measurements on physical evidence that can lead to more accurate and consistent decisions and the importance of carefully designed studies in the evaluation of forensic evidence.

Date: 2015
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1111/insr.12069 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:istatr:v:83:y:2015:i:1:p:111-134

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0306-7734

Access Statistics for this article

International Statistical Review is currently edited by Eugene Seneta and Kees Zeelenberg

More articles in International Statistical Review from International Statistical Institute Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().