Bayes’s Theorem And Weighing Evidence by Juries

نویسنده

  • A. P. Dawid
چکیده

At first sight, there may appear to be little connection between Statistics and Law. On closer inspection it can be seen that the problems they tackle are in many ways identical — although they go about them in very different ways. In a broad sense, each subject can be regarded as concerned with the Interpretation of Evidence. I owe my own introduction to the common ground between the two activities to my colleague William Twining, Professor of Jurisprudence at University College London, who has long been interested in probability in the law. In our discussions we quickly came to realise that, for both of us, the principal objective in teaching our students was the same: to train them to be able to interpret a mixed mass of evidence. That contact led to my contributing some lectures on uses and abuses of probability and statistics in the law to the University of London Intercollegiate LlM course on Evidence and Proof (and an Appendix on “Probability and Proof” to Anderson and Twining (1991)), as well as drawing me into related research (Dawid 1987; Dawid 1994; Dawid and Mortera 1996; Dawid and Mortera 1998). To my initial surprise, I found here a rich and stimulating source of problems, simultaneously practical and philosophical, to challenge my logical and analytical problem-solving skills. For general background on some of the issues involved, see Eggleston (1983); Robertson and Vignaux (1995); Aitken (1995); Evett and Weir (1998); Gastwirth (2000). The current state of legal analysis of evidence seems to me similar to that of science before Galileo, in thrall to the authority of Aristotle and loth to concede the need to break away from old habits of thought. Galileo had the revolutionary idea that scientists should actually look at how the world behaves. It may be equally revolutionary to suggest that lawyers might look at how others have approached the problem of interpretation of evidence, and that they might even have something to learn from them. It is my strong belief (though I do not

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تاریخ انتشار 2001