Forensic statistics is the application of probability models and statistical techniques to scientific evidence, such as DNA evidence,[1] and the law. In contrast to "everyday" statistics, to not engender bias or unduly draw conclusions, forensic statisticians report likelihoods as likelihood ratios (LR). This ratio of probabilities is then used by juries or judges to draw inferences or conclusions and decide legal matters.[1] Jurors and judges rely on the strength of a DNA match, given by statistics, to make conclusions and determine guilt or innocence in legal matters.[2]
In forensic science, the DNA evidence received for DNA profiling often contains a mixture of more than one person's DNA. DNA profiles are generated using a set procedure, however, the interpretation of a DNA profile becomes more complicated when the sample contains a mixture of DNA. Regardless of the number of contributors to the forensic sample, statistics and probabilities must be used to provide weight to the evidence and to describe what the results of the DNA evidence mean. In a single-source DNA profile, the statistic used is termed a random match probability (RMP). RMPs can also be used in certain situations to describe the results of the interpretation of a DNA mixture.[3] Other statistical tools to describe DNA mixture profiles include likelihood ratios (LR) and combined probability of inclusion (CPI), also known as random man not excluded (RMNE).[4]
Computer programs have been implemented with forensic DNA statistics for assessing the biological relationships between two or more people. Forensic science uses several approaches for DNA statistics with computer programs such as; match probability, exclusion probability, likelihood ratios, Bayesian approaches, and paternity and kinship testing.[5]
Although the precise origin of this term remains unclear, it is apparent that the term was used in the 1980s and 1990s.[6] Among the first forensic statistics conferences were two held in 1991 and 1993.[7]
^ abGill, Richard. "Forensic Statistics: Ready for Consumption?" (PDF). Mathematical Institute, Leiden University.
^Perlin, Mark (2015). "Inclusion probability for DNA mixtures is a subjective one-sided match statistic unrelated to identification information". Journal of Pathology Informatics. 6 (59): 59. doi:10.4103/2153-3539.168525. PMC 4639950. PMID 26605124.
^Butler, John (2005). Forensic DNA Typing (2nd ed.). Elsevier Academic Press. pp. 445–529.
^Butler, John (2015). Advanced Topics in Forensic DNA Typing: Interpretation. San Diego, CA: Elsevier Inc. pp. 213–333.
^Fung, Wing Kam (2006). "On Statistical Analysis Of Forensic DNA: Theory, Methods And Computer Programs". Forensic Science International. 162 (1–3): 17–23. doi:10.1016/j.forsciint.2006.06.025. PMID 16870375.
^Valentin, J (1980). "Exclusions and attributions of paternity: practical experiences of forensic genetics and statistics". Am J Hum Genet. 32 (3): 420–31. PMC 1686081. PMID 6930157.
^Aitken C. G. G., Taroni F. (2004) Statistics and the Evaluation of Evidence for Forensic Scientists, John Wiley and Sons.
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