Ron Kohavi, Diane Tang, & Ya Xu (2020)
Cambridge University Press.
DOI: https://doi.org/10.1017/9781108653985
Abstract. The definitive practitioner guide to large-scale A/B testing. Covers metric design, sample-size calculation, sequential testing, interaction effects, and the many subtle pitfalls of running online experiments at scale, drawing on the authors' experience at Microsoft, Google, and LinkedIn.
Tags: ab-testing statistics