Causation, Statistics, and the Law

More and more, judges and juries are being asked to handle torts and other cases in which establishing liability involves understanding large bodies of complex scientific evidence. When establishing causation is involved, the evidence can be diverse, can involve complicated statistical models, and can seem impenetrable to non-experts. Since the decision in Daubert v. Merril Dow Pharms., Inc. in 1993, judges cannot simply admit expert testimony and other technical evidence and let jurors decide the verdict. Judges now must rule on which experts are admissible and which are inadmissible, and they must base their ruling at least partly on the status of the scientific evidence about which the expert will testify. 2 This article is intended to provide judges with an accessible methodological overview of causal science. Part I of this article will explain the nature of causal claims in the realm of judicial evidence. Part II will address why these claims are difficult to prove scientifically and identify the different kinds of evidence typically used to prove causal claims. Part III will explain how the discipline of statistics fits into the science of establishing causal claims. Finally, part IV will