Effective Use of Sampling and Extrapolation to Prove Liability in FCA Litigation: A 2017 Perspective


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SKU: 2017-01-26 Category: Tags: , ,


In False Claims Act (FCA) cases, both the government and private plaintiffs suing on behalf of the government are seeking to use streamlined approaches, like statistical sampling and extrapolation, to prove liability and  damages in complex cases, especially when individualized proof of multiple claims is burdensome and impractical. Statistical sampling draws conclusions about a large data set from the characteristics of a (small) sample of that data set. Extrapolation, on the other hand, draws inferences about a larger population from the analysis of a smaller sample.  Both approaches involve identifying a representative sample of claims and using that sample to draw inferences and make conclusions about the larger pool of claims, which may themselves remain individually unidentified.

How might these statistical methods, commonplace in other civil contexts, affect the future of FCA litigation?

In this LIVE Webcast, a seasoned panel of thought leaders, practitioners, and professionals brought together by The Knowledge Group will provide the audience with an in-depth analysis and discussion of the Effective Use of Sampling and Extrapolation in Proving Liability in a FCA Litigation. Speakers will go beyond the basic and present to the audience their expert thoughts and opinions not only on how to maximize the benefits of sampling and extrapolation, but also how to defend an FCA action when sampling is proposed.

Key topics include:

  • Historical Uses of Statistical Sampling and Extrapolation in Complex Civil Litigation
  • Using Statistical Sampling and Extrapolation in Proving FCA Liability
  • Recent Court Decisions
  • Opportunities, Challenges, and Defenses
  • Potential Risks and Best Practices