Statistics and the Evaluation of Evidence for Forensic Scientists

By C. Aitken, Franco Taroni. 2004

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How researchers see this paper

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Computational Intelligence and Feature Selection - Rough and Fuzzy Approaches (2008, methodology): “This motivates the use of two-level univariate models that can incorporate such information effectively [1].”
Evaluation of trace evidence in the form of multivariate data (2004, methodology): “As is well documented elsewhere (e.g. Aitken (1995)) this source of criticism can be avoided through the use of the likelihood ratio.”
Probabilistic evaluation of handwriting evidence: likelihood ratio for authorship (2008, background): “Its use in forensic science was widely discussed in Aitken and Taroni (2004).”
What role should investigative facts play in the evaluation of scientific evidence? (2011, background): “It can be demonstrated mathematically that the probative value of forensic evidence, as measured by the likelihood ratio, decreases as the FPP increases, other factors being equal 35 .”
Bayes's theorem and weighing evidence by juries (2002, background): “For general background on some of the issues involved, see Eggleston (1983); Robertson and Vignaux (1995); Aitken (1995); Evett and Weir (1998); Gastwirth (2000).”
Dismissal of the illusion of uncertainty in the assessment of a likelihood ratio (2016, background): “Kernel density estimation is not a novel approach in forensic science, and several applications can be found (see, e.g. Aitken and Taroni, 2004).”