Statistical Analysis and Interpretation of Data Commonly Used in Employment Law Litigation

BY C. PAUL WAZZAN & KENNETH D. SULZER

Employment law litigation, such as “wage and hour” misclassification class action lawsuits and “overtime” or “off the clock” lawsuits, has increased in frequency over the past few years as a result of many factors, including increased awareness by the Plaintiffs’ bar and new developments in the law. In many of these cases, the use of statistical analysis is increasingly common. The California Supreme Court, in Sav-on Drug Stores, Inc. v. Superior Court of Los Angeles County (“Sav-on”) encouraged trial courts to adopt “procedurally innovative” methods, including survey results and the statistical analysis thereof, for evaluating class certification. In Dukes v. Wal-Mart Store Inc. (“Dukes”) plaintiffs sought certification of a class of as many as one million women who asserted gender discrimination claims. The large number of potential plaintiffs in (“Dukes”), virtually requires statistical analysis. This article provides legal scholars and practitioners with a vocabulary to address the statistical analysis and interpretation of data commonly used in employment and labor law litigation. We describe tests of significance, random sampling, and required sample size…
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