Teaching Statistics at Google-Scale

Nicholas Chamandy, Omkar Muralidharan and Stefan Wager

The American Statistician, 2015, vol. 69, issue 4, 283-291

Abstract: Modern data and applications pose very different challenges from those of the 1950s or even the 1980s. Students contemplating a career in statistics or data science need to have the tools to tackle problems involving massive, heavy-tailed data, often interacting with live, complex systems. However, despite the deepening connections between engineering and modern data science, we argue that training in classical statistical concepts plays a central role in preparing students to solve Google-scale problems. To this end, we present three industrial applications where significant modern data challenges were overcome by statistical thinking.[Received December 2014. Revised August 2015.]

Date: 2015
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DOI: 10.1080/00031305.2015.1089790

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