UNIVERSITY of PENNSYLVANIA LAW REVIEW

This Article radically rethinks the treatment of statistical estimation evidence in civil litigation, focusing for convenience on the federal courts. It proposes an approach that harmonizes legal standards and statistical concepts, replacing the arbitrary and elevated standards of conventional hypothesis testing with an approach that fits what we otherwise think the preponderance standard means. Through careful argumentation using Bayesian hypothesis testing, the Article offers a fundamental default rule for statistical estimation evidence: if the evidence comes from a credibly designed and implemented study, then it is presumptively admissible and enough to withstand motions for judgment under either Rule 50 or Rule 56, whenever it points in the direction of the party offering it. In many situations, the fundamental default rule may be cast as the policy that evidence is legally sufficient and presumptively admissible whenever it yields a finding of statistical significance at the 50 percent level-equivalently, whenever its p-value is less than 0.5. Thus, the Article indicates that many courts' current practice is far too strict with respect to statistical estimation evidence. The Article also discusses the appropriate gatekeeping role for federal district courts under Federal Rules of Evidence 403 and 702, and it engages the question of when courts might legitimately move away from the fundamental default rule for policy reasons.