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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[A probability is] subjective [and it] means the degree of belief (as actually held by someone, on the ground of his whole knowledge, experience, information) regarding the truth of a sentence or event, картинка 105 (a fully specified single event or sentence, whose truth or falsity is, for whatever reason, unknown to that person). (p. 45)

1.3.1 The Frequentist Method

Consider a consignment of compact disks (CDs), containing картинка 106disks. The consignment is said to be of size Statistics and the Evaluation of Evidence for Forensic Scientists - изображение 107. It is desired to make inferences about the proportion Statistics and the Evaluation of Evidence for Forensic Scientists - изображение 108( Statistics and the Evaluation of Evidence for Forensic Scientists - изображение 109) of the consignment which is pirated. It is not practical to inspect the whole consignment so a sample of size картинка 110, where картинка 111is inspected.

The frequentist method assumes that the proportion картинка 112of the consignment that is pirated is unknown but fixed. The data, that is the number of CDs in the sample that are pirated, are variable. A so‐called confidence interval is calculated. The name confidence is used since no probability can be attached to the uncertain event that the interval contains картинка 113. These ideas are discussed further in Chapter 4.

The frequentist method derives its name from the relative frequency definition of probability. The probability that a particular event, картинка 114, say, occurs is defined as the relative frequency of the number of occurrences of event картинка 115compared with the total number of occurrences of all possible events, over a long run of observations, conducted under identical conditions of all possible events. The limitations of such a definition are presented in Section 1.7.4.

For example, consider tossing a coin картинка 116times. It is not known if the coin is fair. The outcomes of the картинка 117tosses can be used as information from which the probability of a head occurring on an individual toss may be assigned. There are two possible outcomes, heads ( картинка 118) and tails ( картинка 119). Let картинка 120be the number of картинка 121and be the number of such that Then the probability of tossing a head on an indivi - фото 122be the number of such that Then the probability of tossing a head on an individual toss of the - фото 123such that Then the probability of tossing a head on an individual toss of the coin is - фото 124Then the probability of tossing a head on an individual toss of the coin is defined as the limit as Statistics and the Evaluation of Evidence for Forensic Scientists - изображение 125of the fraction Statistics and the Evaluation of Evidence for Forensic Scientists - изображение 126. The frequentist approach relies on a belief in the long‐run repetition of trials 3 under identical conditions. This is an idealised situation, seldom, if ever, realised in practice. More discussion on the interpretation of such a result is given in Section 3.6.

The way in which statistics and probability may be used to evaluate evidence is the theme of this book. Care is required. Statisticians are familiar with variation, as are forensic scientists who observe it in the course of their work. Lawyers, however, prefer certainties. A defendant is found guilty or not guilty (or also, in Scotland, not proven ). The scientist's role is to testify to the worth of the evidence, the role of the statistician and this book is to provide the scientist with a quantitative measure of this worth. It is shown that there are few forms of evidence that are so definite that statistical treatment is neither needed nor desirable. It is up to other people (the judge and/or the jury) to use this information as an aid to their deliberations. It is for neither the statistician nor the scientist to pass judgement (Kind 1994).

The use of these ideas in forensic science is best introduced through the discussion of several examples. These examples will provide a constant theme throughout the book. Consideration in detail of populations from which the criminal may be thought to have come, to which reference is made in the following text, are discussed in Section 6.1.1 where they are called relevant populations . The value of evidence is measured by a statistic known as the likelihood ratio and its logarithm. These are introduced in Sections 2.3and 2.4.

1.3.2 Stains of Body Fluids

Example 1.1A crime is committed. A bloodstain is found at the scene of the crime. All innocent explanations for the presence of the stain are eliminated. A PoI is found. Their DNA profile is established and found to correspond to that of the crime stain. What is the evidential value of this correspondence? This is a very common situation yet the answer to the question provides plenty of opportunity for discussion of the theme of this book.

Certain other questions need to be addressed before this particular one can be answered. Where was the crime committed, for example? Does it matter? Does the value of the evidence of the bloodstain change depending on where the crime was committed?

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