Franco Taroni - Statistics and the Evaluation of Evidence for Forensic Scientists

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T
he leading resource in the statistical evaluation and interpretation of forensic evidence
The third edition of 
 is fully updated to provide the latest research and developments in the use of statistical techniques to evaluate and interpret evidence. Courts are increasingly aware of the importance of proper evidence assessment when there is an element of uncertainty. Because of the increasing availability of data, the role of statistical and probabilistic reasoning is gaining a higher profile in criminal cases. That’s why lawyers, forensic scientists, graduate students, and researchers will find this book an essential resource, one which explores how forensic evidence can be evaluated and interpreted statistically. It’s written as an accessible source of information for all those with an interest in the evaluation and interpretation of forensic scientific evidence. 
Discusses the entire chain of reasoning–from evidence pre-assessment to court presentation; Includes material for the understanding of evidence interpretation for single and multiple trace evidence; Provides real examples and data for improved understanding. Since the first edition of this book was published in 1995, this respected series has remained a leading resource in the statistical evaluation of forensic evidence. It shares knowledge from authors in the fields of statistics and forensic science who are international experts in the area of evidence evaluation and interpretation. This book helps people to deal with uncertainty related to scientific evidence and propositions. It introduces a method of reasoning that shows how to update beliefs coherently and to act rationally. In this edition, readers can find new information on the topics of elicitation, subjective probabilities, decision analysis, and cognitive bias, all discussed in a Bayesian framework.

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(1.12) This is sometimes known as the extension of the conversation Lindley 1991 An - фото 597

This is sometimes known as the extension of the conversation (Lindley 1991)

An example for blood types and paternity cases is given by Lindley (1991). Consider two possible groups, картинка 598(Rh картинка 599) and картинка 600(Rh+) for the father, so here картинка 601. Assume the relative frequencies of the two groups are картинка 602and картинка 603, respectively. The child is Rh картинка 604(event картинка 605) and the mother is also Rh картинка 606(event картинка 607). The probability of interest is the probability a Rh Statistics and the Evaluation of Evidence for Forensic Scientists - изображение 608mother will have a Rh Statistics and the Evaluation of Evidence for Forensic Scientists - изображение 609child, in symbols Statistics and the Evaluation of Evidence for Forensic Scientists - изображение 610. This probability is not easily derived directly but the derivation is fairly straightforward if the law of total probability is invoked to include the father.

(1.13) This is a generalisation of the law to include information If both parents - фото 611

This is a generalisation of the law to include information картинка 612. If both parents are Rh картинка 613, event ( картинка 614and then the child is Rh with probability 1 so If the father is Rh the mot - фото 615), then the child is Rh with probability 1 so If the father is Rh the mother is still Rh event - фото 616with probability 1, so If the father is Rh the mother is still Rh event then - фото 617. If the father is Rh+ (the mother is still Rh event then Assume that parents mate at random with respect to the Rhesu - фото 618), event then Assume that parents mate at random with respect to the Rhesus quality - фото 619, then Statistics and the Evaluation of Evidence for Forensic Scientists - изображение 620. Assume that parents mate at random with respect to the Rhesus quality. Then Statistics and the Evaluation of Evidence for Forensic Scientists - изображение 621, the relative frequency of Rh in the population independent of Similarly the relative frequency of Rh - фото 622in the population, independent of Similarly the relative frequency of Rh in the population These - фото 623. Similarly, the relative frequency of Rh in the population These probabilities can now - фото 624, the relative frequency of Rh+ in the population. These probabilities can now be inserted in ( 1.13) to obtain

for the probability that a Rh mother will have a Rh child This result is - фото 625

for the probability that a Rh картинка 626mother will have a Rh картинка 627child. This result is not intuitively obvious, unless one considers the approach based on the law of total probability.

An example using DNA profiles is given in Evett and Weir (1998). According to the 1991 census, the New Zealand (NZ) population consists of 83.47% Caucasians, 12.19% Maoris, and 4.34% Pacific Islanders; denote the event that a person chosen at random from the 1991 NZ population is Caucasian, Maori, or Pacific Islander as Ca , Ma , and Pa , respectively. The probabilities of finding the same YNH24 genotype картинка 628(event картинка 629) in a crime sample for a Caucasian, Maori, or Pacific Islander are 0.012, 0.045, and 0.039, respectively. These values are the assessments for the following three conditional probabilities: Then the probability of finding the YNH24 genotype in a person taken at - фото 630Then the probability of finding the YNH24 genotype, in a person taken at random from the whole population of New Zealand is A - фото 631, in a person taken at random from the whole population of New Zealand is

A further extension of this law to consider probabilities for combinations of - фото 632

A further extension of this law to consider probabilities for combinations of genetic marker systems in a racially heterogeneous population has been given by Walsh and Buckleton (1988). Let картинка 633and картинка 634be two genetic marker systems with realisations картинка 635and картинка 636, картинка 637, and картинка 638. Let картинка 639and картинка 640be two mutually exclusive and exhaustive subpopulations such that a person from the population belongs to one and only one of картинка 641and картинка 642. Let картинка 643and картинка 644be the probabilities that a person chosen at random from the population belongs to and to respectively Then Within each subpopulation - фото 645and to respectively Then Within each subpopulation and - фото 646, respectively. Then Within each subpopulation and are independent so that the probability an ind - фото 647. Within each subpopulation картинка 648and картинка 649are independent so that the probability an individual chosen at random from one of these subpopulations is of type is simply the product of the individual probabilities Thus However such a - фото 650is simply the product of the individual probabilities. Thus

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