On March 22, 2016, the Supreme Court decided Tyson Foods, Inc. v. Bouaphakeo, affirming a verdict in favor of a certified class under the Fair Labor Standards Act. Importantly, Tyson Foods determined that representative statistical evidence is a permissible means of establishing class-wide liability for purposes of class certification.
In a 6-2 decision, the Supreme Court confirmed that, while no “general rules govern  the use of statistical evidence brought in all class actions,” such evidence “cannot be deemed improper merely because [a] claim is brought on behalf of a class.” The Court explained that statistical sampling is permissible to prove class-wide liability in cases where class members can rely on the same sampling for liability purposes in individual actions. The Supreme Court also confirmed that a district court may rely on expert statistical evidence where that evidence is not specifically challenged in what is frequently referred to as a Daubert motion, referencing the Supreme Court’s decision in Daubert v. Merrell Dow Pharmaceuticals, Inc., 509 U.S. 579 (1993).
The Supreme Court’s decision in Tyson Foods may turn out to be particularly important to antitrust class cases, where liability and damages models frequently rely on expert economic and econometric evidence. As with Tyson Foods, liability and damages in antitrust class cases often rely on statistical evidence or representative samples. These models have been vigorously challenged by the defendants, leading to highly contested class certification battles. The Supreme Court’s approval of statistical sampling in liability and damages models may mark a turning point in class cases, and what may become a less stringent path for plaintiffs on the road to class certification.
See here for a full copy of the Supreme Court’s decision in Tyson Foods, Inc. v. Bouaphakeo, et al.
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