By Grace Renshaw
Edward K. Cheng has been appointed to the Tarkington Chair of Teaching Excellence, a three-year rotating appointment that recognizes outstanding classroom teaching. Since joining Vanderbilt’s law faculty in 2010, Cheng has won three Hall-Hartman Teaching Awards, one for his first-year Torts course and two for his upper-level Evidence course.
The Tarkington Chair was endowed in 1998 by Carlton B. Tarkington ’63 (BA’59), who was Vanderbilt Law School’s 2011 Distinguished Alumnus.
Ed Cheng’s scholarship covers an array of issues in his chosen field of evidence law. But all of his work is focused on one goal: Making sure judges and lawyers get the math right.
Cheng, who was appointed to the Tarkington Chair in 2013, is uniquely qualified to suggest ways in which lawyers and courts can do a better job of addressing the mathematical aspects of legal cases in general, and of interpreting and understanding statistical evidence in particular. His interest in bridging the gap between law and public policy and applied math began during his undergraduate studies at Princeton University, where he earned a certificate from the Woodrow Wilson School for Public and International Affairs in addition to his bachelor’s degree in electrical engineering. He earned a master of science in information systems as a Fulbright Scholar at the London School of Economics and Political Science before earning his J.D. at Harvard Law School, where he was the articles and commentaries chair of the Harvard Law Review.
Cheng has taught and studied evidence law since 2003, when he joined the faculty of Brooklyn Law School after serving as a law clerk to Judge Stephen F. Williams on the U.S. Court of Appeals for the D.C. Circuit and as a Searle Fellow at Northwestern University Law School. To inform his research and teaching, he started work on a Ph.D. in statistics at Columbia University in 2008, earning his master’s degree in 2011. Vanderbilt’s emphasis on interdisciplinary research and multidisciplinary approaches to problem solving was one factor in his decision to join its law faculty in 2010.
Cheng’s strong belief that everyone is capable of using both sides of their brains imbues his teaching with missionary sense of purpose. He wants his students—and American lawyers in general—to approach statistical evidence with a critical eye. “The educational systems in other countries assume that everyone has the capacity to handle nontrivial math problems,” he said. “Our society tends to make people think they are either ‘math people’ or ‘nonmath people.’ People flee from statistics because they flee from math. That becomes a professional handicap for lawyers when so many things are statistically based or driven.”
Cheng’s focus on the way statistics are used as legal evidence is directly related to the increasing reliance of many legal areas on evidence generated by scientific or social scientific studies, much of which is presented as statistics or in terms of probabilities. “Disparate impact employment litigation depends on statistics, as does proof of causation in toxic torts,” he said. “Proper valuation of damages or corporate assets requires quantitative models. And DNA evidence in criminal cases involves vanishingly small random-match probabilities, such as 1 in 4 trillion.”
In his Tarkington lecture, which has since been published in a popular legal journal, The Green Bag [“Fighting Legal Innumeracy,” 17 Green Bag 2D 271 (2014)], Cheng challenged the legal community to reject the premise of the “tired joke” that lawyers “go to law school precisely because they…were never good at math.” Numeracy, the math equivalent of literacy, Cheng asserts, “is a fundamental skill for any intelligent, engaged participant in society, and we lawyers ignore it at our peril.”
Cheng defines legal numeracy as “the ability to comprehend, critically assess and explain” the studies upon which statistical evidence is based, and he highlights a compelling reason for lawyers to avoid bland acceptance of innumeracy: Math errors are all too common in legal cases. “Playing gotcha with typos is practically the official sport of the bench and bar. Yet, lawyers and courts notoriously make incorrect numerical calculations—sometimes caught, sometimes not—but generally without the same snarky rebukes,” he said.
Lawyers who lack the critical skill to analyze statistical evidence tend to be either too accepting of such evidence or too dismissive, according to Cheng. “When faced with statistical information, the innumerate either defer, relying entirely on experts and being at their mercy, or conclude that statistics are basically manipulable lies or incomprehensible gibberish not worth taking time to understand,” he said.
In its 1993 decision in Daubert v. Merrell Dow Pharmaceuticals, the Supreme Court rejected the deference strategy and made judges responsible for determining whether to admit evidence involving the testimony of expert witnesses and study results. “Conventionally, Daubert is thought of as a watershed case that eliminated junk science and charlatans from the courtroom,” Cheng said. “In fact, Daubert changed the nature of debate over scientific evidence in courts. Gone are the days of deference in which the ipse dixit of the expert was sufficient. In its place, Justice Blackmun asked judges to be the gatekeepers—a new role that required judges to understand, grapple with, and assess expertise critically.”
Cheng believes that Daubert implicitly also requires that attorneys understand and analyze the statistical information they use as evidence. “Daubert tasks all lawyers with the goal of numeracy and the critical handling of statistical studies,” he said. “We thus have the responsibility of acquiring and helping others acquire this skill set.”
To promote greater numeracy in the legal profession, Cheng suggests a simple strategy: Keep asking questions. “We need to demand, without embarrassment, that quantitative researchers not only explain the conclusions of their studies, but also how and why the methods work and their limitations,” he said. “If the expert cannot explain things to your satisfaction, the problem is not you; it’s the expert.”
He also believes the onus is on law schools to devote more attention to teaching numeracy skills. “Here, my proposal is emphatically not to replace Torts with regression analysis,” said Cheng, who teaches Torts as well as Evidence. “However, there are many opportunities to teach numeracy skills. For example, Federal Rule of Evidence 803(4) establishes an exception to the hearsay rules for statements made for purposes of medical diagnosis. The rationale is that people tend not to lie to doctors because telling the truth is critical to proper treatment. The Eighth Circuit has held that the rule, however, does not apply to a 3-year-old, who is too young to understand the need to be truthful to doctors. The casebook refers students to research that suggests that 5- and 6-year-olds have a better understanding of the importance of telling physicians the truth. Instead of simply deferring to that conclusion, I could take a few minutes to force my students to be critical: Was the sample size of 40 children sufficient? Was the sample representative, or did it skew toward especially articulate children? After all, only certain parents of certain children will take them to be interviewed. Were the observed differences large enough to reach a definitive conclusion? And if we think the answer to any of these questions is no, what are the implications for courts the next time they hear such cases?”
Students in Cheng’s Torts and Evidence classes will likely face many such questions in the future.