In employment discrimination cases, courts are frequently faced with statistical evidence that does not go beyond a comparison of simple averages. Economists and statisticians have various tools at their disposal to dig deeper and analyze what lies behind such simple averages. To address the limitations of relying solely on simple averages and to examine how such statistics may conceal actual patterns in the data, NERA hosted this seminar in Los Angeles on 23 October 2008.
NERA Vice Presidents Dr. Elizabeth Newlon and Dr. Kristin Terris discussed how to recognize potentially misleading statistics and what to do about them with Travis Gemoets, a Partner at Jeffer, Mangels, Butler & Marmaro, LLP. The seminar also addressed how statistical techniques that appear to move beyond simple averages (such as regression analysis) are vulnerable to similar dangers and can obscure, rather than illuminate, the truth. The panelists examined these issues in the context of discrimination claims that are class actions, as well as claims that involve a smaller group of plaintiffs. They also discussed recent developments in the law as they affect the application of statistical and economic evidence to discrimination claims, as well as in other employment-related matters, including wage and hour class actions.