Applications of Probability Theory in Criminalistics

Kingston, Charles

doi:10.1080/01621459.1965.10480776

Cited by 23 publications

(5 citation statements)

References 6 publications

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“…In general, conditional on X =x, the probability of guilt is 1/(1 +x). Averaging over the distribution of X gives the probability of the suspect's guilt: Kingston (1965) and Cullison (1969) argued that initially the total number Z of 'Y'-bearers, innocent or not, has the binomial distribution with parameters N + 1 and p. After noting that the criminal has 'Y', we know that the total number of Tvbearers is non-zero and hence (2) for which there does not appear to be a simple expression.…”

Section: Original Island Problemmentioning

confidence: 99%

Inference in Forensic Identification

Balding¹,

Donnelly²

1995

Journal of the Royal Statistical Society. Series A (Statistics

102

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SUMMARY The problem of quantifying the weight of evidence in forensic identification is addressed. The essence of the problem is abstracted in a simple paradigm, the analysis of which yields valuable insights and highlights important distinctions. A special case of this analysis gives a resolution of the so‐called island problem. The paradigm is extended to assess the effects of several features which may be important in practical situations, such as possible alibis, heterogeneous populations of potential suspects and informative protocols for finding suspects. The analyses of the paper clarify several issues pertaining to the weight of evidence associated with matching deoxyribonucleic acid (DNA) profiles and raise some new concerns. In addition, established concerns regarding the incorrect interpretation of probabilistic evidence by juries are discussed in the DNA profile context.

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Section: Original Island Problemmentioning

confidence: 99%

Inference in Forensic Identification

Balding¹,

Donnelly²

1995

Journal of the Royal Statistical Society. Series A (Statistics

102

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“…The general framework of the two-stage approach was first briefly mentioned by Kirk (1953) and Kingston (1965), and was formally described by Parker (1966;1967) and Parker and Holford (1968). Parker breaks down the forensic inference process into two stages, which he describes as the similarity stage, and the discrimination stage.…”

Section: Overview Of Parker's Two-stage Approachmentioning

confidence: 99%

Two-stage approach for the inference of the source of high-dimension and complex chemical data in forensic science

Ausdemore,

Neumann,

Saunders

et al. 2018

Preprint

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Forensic scientists are often criticised for the lack of quantitative support for the conclusions of their examinations. While scholars advocate for the use of a Bayes factor to quantify the weight of forensic evidence, it is often impossible to assign the necessary probability measures to perform likelihood-based inference for high-dimensional and complex data. To address this issue, we revisit a two-stage inference framework and leverage the properties of kernel functions to offer a method that allows for statistically supporting the inference of the identity of source of sets of trace and control objects by way of a single test. Our method is generic in that it can be easily tailored to any type of data encountered in forensic science or pattern recognition, and our method does not depend on the dimension or the type of the considered data. The application of our method to paint evidence shows that this type of evidence carries substantial probative value. Finally, our approach can easily be extended to other evidence types such as glass, fibres and dust.

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“…The use of probability theory in judicial decision‐making attracted particular interest through an array of influential articles published in US forensic science and legal literature in the 1960s and early 1970s (Kingston 1965a,b; Kaplan 1968; Finkelstein and Fairley 1970; Tribe 1971). In particular, much discussion focused on the suitability of Bayes Theorem (Bayes Theorem takes the general form): Or, in mathematical terms: as a means of evaluating evidence to overcome the risks of misusing statistics in courtroom deliberations, as exemplified in controversial cases such as People vs Collins (This case involved the trial of an inter‐racial couple for a robbery in California of an elderly woman.…”

Section: Enacting Epistemic Risk Management In Forensic Sciencementioning

confidence: 99%

Managing Epistemic Risk in Forensic Science: Sociological Aspects and Issues

Lawless

2010

Sociology Compass

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The last decades have seen a notable increase in the use of scientific evidence in criminal investigation, a development which has captured the imagination of the media, publics and policymakers alike. Yet behind the authoritative image of forensic science lies a highly fluid and indeterminate landscape which invites sociological interest. In what follows, I aim to provide a sense of why it holds appeal to sociology, and to also outline a more updated research agenda in the light of continuing developments and deliberation within both sociological and forensic scientific circles. This renewed agenda revolves around the topic of risk. I outline recent developments which represent new approaches to the problem of epistemic risk in forensic science. With reference to a specific example (the 'Case Assessment and Interpretation' method of evidence assessment), I argue for the importance of studying risk-aware practices in forensic investigation, and how these help to reveal further how forensic science can be regarded as a complicated, heterogeneous and highly socialised human activity, in stark contrast to the immutable and technologically sophisticated image often promulgated in popular accounts.

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Applications of Probability Theory in Criminalistics

Cited by 23 publications

References 6 publications

Inference in Forensic Identification

Inference in Forensic Identification

Two-stage approach for the inference of the source of high-dimension and complex chemical data in forensic science

Managing Epistemic Risk in Forensic Science: Sociological Aspects and Issues

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