Computing in the Statistics Curricula

Abstract

The nature of statistics is changing significantly with many opportunities to broaden the discipline and its impact on science and policy. To realize this potential, our curricula and educational culture must change. While there are opportunities for significant change in many dimensions, we focus more narrowly on computing and call for computing concepts to be integrated into the statistics curricula at all levels. Computational literacy and programming are as fundamental to statistical practice and research as mathematics. We advocate that our field needs to define statistical computing more broadly to include advancements in modern computing, beyond traditional numerical algorithms. Information technologies are increasingly important and should be added to the curriculum, as should the ability to reason about computational resources, work with large datasets, and perform computationally intensive tasks. We present an approach to teaching these topics in combination with scientific problems and modern statistical methods that focuses on ideas and skills for statistical inquiry and working with data. We outline the broad set of computational topics we might want students to encounter and offer ideas on how to teach them. We also discuss efforts to share pedagogical resources to help faculty teach this modern material (including supplemental materials).