Various aspects of the role of probabilistic reasoning in the evaluation of evidence are described. These include relative frequencies, discriminating power, significance tests and likelihood ratios, and comments on new developments to aid evidence evaluation. The relevance of all these concepts for soil evaluation is considered as appropriate. It is shown that a procedure based on the likelihood ratio emphasises that information from answers to two opposing and relevant questions needs to be considered. It is shown that the likelihood ratio is the factor which converts a prior odds in favour of a prosecution proposition into a posterior odds. The importance of considering evidence at various levels, source, activity and crime, of propositions are discussed. At present, it is not possible to develop models for likelihood ratios in soil analyses in a way that is available for the elemental analyses of glass fragments or the chemical analyses of drug samples. It is shown that the methodology models variability in characteristics in such a way as to account for variation both between source and within source so that the effect on the odds in favour of the ultimate issue can be measured on a continuous scale. Work that is necessary to be done in order to develop likelihood ratios is highlighted together with the difficulties that are particular to soil analyses.
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References
Aitken CGG and Taroni F (2004) Statistics and the evaluation of evidence for forensic scientists, John Wiley & Sons, Chichester.
Cook R, Evett IW, Jackson G, Jones PJ and Lambert JA (1998a) A model for case assessment and interpretation. Science and Justice 38:151–156.
Cook R, Evett IW, Jackson G, Jones PJ and Lambert JA (1998b) A hierarchy of propositions:deciding which level to address in casework. Science and Justice 38:231–239.
Cook R, Evett IW, Jackson G, Jones PJ and Lambert JA (1999) Case pre-assessment and review of a two-way transfer case. Science and Justice 39:103–122.
Darboux JG, Appell PE and Poincaré JH (1908) Examen critique des divers syst∝emes ou etudes graphologiques auxquels a donne lieu le bordereau. In: L'affaire Drefus—La revision du procμes de Rennes—enquete de la chambre criminelle de la Cour de Cassation. Ligue francaise des droits de l'homme et du citoyen, Paris, France:499–600.
Darroch J (1987) Probability and criminal trials; some comments prompted by the Splatt trial and The Royal Commission. The Professional Statistician 6:3–7.
Dudley RJ and Smalldon KW (1978) The comparison of distributional shapes with particular reference to a problem in forensic science. International Statistical Review 46:53–63.
Evett IW (1984) A quantitative theory for interpreting transfer evidence in criminal cases. Applied Statistics 33:25–32.
Evett IW (1991) Interpretation: a personal odyssey. In: The use of statistics in forensic science (Eds. CGG Aitken and DA Stoney), Ellis Horwood, Chichester:9–22.
Fairley WB and Mosteller W (1977) Statistics and public policy, Addison-Wesley, London:355–379.
Lark RM and Rawlins BG (2008) Can we predict the provenance of a soil sample for forensic purposes by reference to a spatial database? European Journal of Soil Science 59:1000–1006.
Meier P and Zabell S (1980) Benjamin Pierce and the Howland will. Journal of the American Statistical Association 75:497–506.
Neumann C, Champod C, Puch-Solis R, Egli N, Anthonioz A and Bromage-Griffths A (2007) Computation of likelihood ratios in fingerprint identification for configurations of any number of minutiae. Journal of Forensic Sciences 52:54–64.
Parker JB and Holford A (1968) Optimum test statistics with particular reference to a forensic science problem. Applied Statistics 17:237–251.
Pye K (2007) Geological and soil evidence, forensic applications, CRC, Boca Raton, FL.
Rawlins BG, Kemp SJ, Hodgkinson EH, Riding JB, Vane CH, Poulton C and Freeborough K (2006) Potential and pitfalls in establishing the provenance of earth-related samples in forensic identification. Journal of Forensic Sciences 51:832–845.
Saks MJ, Koehler JJ (2005) The coming paradigm shift in forensic identification science. Science 309:892:895.
Taroni F, Bozza S and Aitken CGG (2005) Decision analysis in forensic science. Journal of Forensic Sciences 50:894–905.
Taroni F, Aitken CGG, Garbolino P and Biedermann A (2006) Bayesian networks and probabilistic inference in forensic science, John Wiley & Sons, Chichester.
Thompson WC and Schumann EL (1987) Interpretation of statistical evidence in criminal trials. The prosecutor's fallacy and the defence attorney's fallacy. Law and Human Behaviour 11:167–187.
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Aitken, C.G.G. (2009). Some Thoughts on the Role of Probabilistic Reasoning in the Evaluation of Evidence. In: Ritz, K., Dawson, L., Miller, D. (eds) Criminal and Environmental Soil Forensics. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9204-6_3
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