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Category: Keynote

Published: 01 July 2026

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Foreword by Michael I. Jordan

What is an “e-value” and why has it become an object of intense study in statistics and in the allied fields of machine learning, signal processing, and econometrics? To briefly introduce the basic idea, let us consider one of the core problems in statistics – the “hypothesis testing problem” of deciding whether observed data is consistent with some particular data-generating mechanism (often referred to as a “null hypothesis”) or is better explained by another mechanism (referred to as an “alternative hypothesis”). This problem is addressed by defining some function of the data (a “statistic”) whose distribution is as different as possible under the null and the alternative. Given an observed value of such a statistic, one then makes a choice between the two distributions, doing so in a way that minimizes the probability of errors. Classical statistical theory provides a unifying framework – the “p-value” – by which the choice between the null and alternative hypotheses reduces to a thresholding procedure.