Statistics and Trace Evidence: The Tyranny of Numbers
Houck, Max M., Forensic Science Communications
The public perception of science allies it closely with mathematics, and the application of statistics to forensic DNA analysis has reinforced this perception. Numbers, however, are not required for the scientific process. All science, including forensic science, is a method of understanding the world around us, and quantitation is only one tool to assist that methodology. Yet, the public and the courts expect forensic scientists, including trace evidence examiners, to use mathematics and statistics regularly, based largely on the DNA model. Recent articles and court rulings have even suggested that without statistics, trace evidence may not be acceptably scientific.
This expectation is fraught with pitfalls that could adversely affect the accuracy of evidentiary reports presented in court. The foundational data upon which trace evidence statistics might be based differ radically from those used in DNA statistical calculations. If statistics are to be applied to trace evidence, they must be applied in a way appropriate to the discipline, unbiased in interpretation, and accessible to the trier of fact.
DNA Analysis = Forensic Science
You might not expect an article on trace evidence to begin by discussing DNA, but the advent of forensic DNA analysis has produced significant changes in the perception, both public and professional, of forensic science. This is particularly true of trace evidence, where numerous attempts at statistical evaluation or data gathering have been published (Home and Dudley 1980; Biermann and Grieve 1996a, 1996b; Biermann and Grieve 1998; Curran et al. 1998). No one model has been widely adopted, particularly in the United States, and yet legal experts, attorneys, and the courts are increasingly interested in using statistical methods to increase the reliability of trace evidence. The comments most often heard by trace analysts, "Why can't you calculate a number like DNA?", and "Trace evidence is only 'could have' evidence," adequately frame the dilemma we face. We cannot provide the same statistical frequencies as our DNA colleagues, but we have observed that a positive association of paint, hair, or fibers is a significant event that is not likely to be duplicated at random. So, then, if trace evidence analysts know this, why can't they use statistics to help convey this information to the jury?
How Do We Know All Ravens Are Black?
Science has the ancient philosophical traditions of Greece, Rome, and the Middle East as its basis. The Greek philosophers, beginning with the mathematician Thales (ca. 600 B.C.) and including Aristotle (384-322 B.C.), were primarily rationalists, proposing the solutions to scientific questions by focused reasoning, what we now call deduction. Thales in particular was adamant in accepting only results that had been established by mathematical reasoning. Because all mathematical proofs are by their nature deductive (Kline 1967), this, along with other social factors in ancient Greek civilization, led to an inescapable reliance on deductive logic. The success of these ancient scholars in their explanations led to "an overrating of a purely rational approach" (Mayr 1982), reaching its pinnacle with the French philosopher and mathematician Rene Descartes (1596-1650). Like Thales, Descartes' ideal of scientific reasoning was a mathematical proof. This perception persists even today, particularly in the popular concept of science. It has persisted not only in the physical sciences, where mathematical proofs are often possible, but also in the biological sciences (Mayr 1982). The "tyranny of numbers," the trenchant belief that science is best expressed through mathematics, overshadows the potential explanatory power many disciplines have, simply because a mathematical value is expected but may not be possible. The Scottish historian David Hume (1711-1776) noted, for example, that in many, if not the majority of cases, it is impossible for biologists to provide proofs of pure mathematical certainty because of the complex nature of living systems (Hemple 1966). …