Legal and statistical aspects of some mysterious clusters

Abstract

SUMMARY Criminal and civil trials often involve events that appear to cluster together in time or space, and the existence and size of the cluster often is interpreted as implying that the occurrence of the events could not be a coincidence. This paper examines the statistical evidence introduced in several cases to show how such mysterious clusters should be interpreted. The paper considers this form of evidence in the context of legal views on the admissibility of evidence about 'similar events', and it suggests a more formal statistical argument that might be used to justify admissibility in one category of cases. The finely chiselled lips parted. He said, 'Mr Bond, they have a saying in Chicago: Once is happenstance. Twice is coincidence. The third time it's enemy action.' These words of the arch villain in Ian Fleming's novel Goldfinger capture a principle firmly etched in the Anglo-American law of evidence: where a purely accidental occurrence would not create liability, proof of similar, prior incidents may be admitted to show that the occurrence is not mere happenstance. In this paper, we describe the situations under which courts allow proof of similar prior incidents to disprove a claim of coincidence. Then, we consider some recent American cases that follow the trend towards greater reliance on forensic statistical assessments described in a National Research Council panel report (Fienberg, 1989) by allowing expert testimony on the probability of an accidental string of similar incidents. Finally, we examine some of the statistical aspects of these calculations and their legal relevance. Our intent is to raise legal and statistical questions regarding the role of a particular form of statistical evidence in actual legal cases, to examine the fit between legal theory and the statistical methodology that has been invoked in such cases and thereby to stimulate further legal and statistical thinking about apparent clusters in legal settings.