GW Law Faculty Publications & Other Works

Document Type

Article

Publication Date

2025

Status

Forthcoming

Abstract

This Article is another offering in the “When the Math Matters” series, seeking to help readers understand use of mathematical and scientific concepts in legal contexts and unpack how to do things better. This Article focuses on the seminal case of Wal- Mart Stores, Inc. v. Dukes, 564 U.S. 338 (2011), describing how the analytical approach to identify whether a class could be certified for purposes of that litigation continues to resonate through recent cases in the federal courts. The Article explains the statistical analysis that lawyers must present to unpack a correlative analysis in similar cases, focusing on adverse impact employment discrimination as an exemplar and seeking to explain the multi-step methodology being used in the courts to address statistical analysis.

Building on previous works in this series, this Article thus presents the analytical framework for lawyers successfully to engage in use of statistics for purposes of class certification to show commonality of the class, particularly in the context of adverse impact employment discrimination. The Article chooses to use adverse impact litigation as an example to understand the statistical analysis because statistics has been fundamental to success in adverse impact litigation for many years, such that the relevant methodologies are well-developed, and the Supreme Court has spoken at some level of detail in that context, explaining the kinds of statistical analysis the Court would consider valid in an extremely large class action like that presented in the Dukes case. Such class actions already arise in a dizzying array of legal contexts, and the Article will offer thoughts on directions to find commonality – the “glue” in the vernacular of the Dukes case – in class action litigation going forward.

GW Paper Series

2025-57

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