Year: 2017
Type: article
Abstract: Introduction to Volume 4We continue the tradition established in Volumes 1 through 3 to bring our readers surveys of the latest advances in the theory and applications of statistics.One of our goals for these volumes is to present articles from senior leaders with an autobiographical flavor.This volume leads with an overview article by one of our discipline's senior scholars, Don Fraser.Don is never one to look back, but he has spent a lifetime thinking about the foundations of statistics, and summarizes here his current thinking on the critical role of p-values as a foundational approach to inference.Don did his graduate studies with John Tukey and Samuel Wilks at Princeton, and has made his career at the University of Toronto, where he has inspired many generations of scholars in statistical science.The strength of statistical undergraduate programs in Canada, and ongoing interest in statistical theory across the country, is due in large measure to Don's leadership.Don was the first winner of the Gold Medal of the Statistical Society of Canada, and in 2011 was appointed Officer of the Order of Canada.The explosive growth of interest in, and availability of, so-called big data is creating a new discipline, data science, that combines mathematical modeling, statistical reasoning, and computational advances with a renewed emphasis on communication and visualization.This, combined with remarkable increases in enrollments in statistics programs, has led to a flurry of new and planned undergraduate programs in data science.In "Curriculum Guidelines for Undergraduate Programs in Data Science," the Park City Math Institute Undergraduate Faculty Group, led by Richard De Veaux, reports recommendations for undergraduate programs in data science.The guidelines provide an aid to navigation for developing a curriculum and capture the importance of data science in this ever-increasingly data-rich world.The authors emphasize that data science combines statistics, computer science, and mathematics, with data at the core, anchored by mathematics and illuminated by computational and statistical approaches.With some adjustments, the proposed undergraduate curriculum is directly relevant to graduate education and to lifelong learning.If you've asked, "What is data science?" or want to open the hood and see what leading experts propose as necessary knowledge, read this article.The emphasis on communication cannot be overestimated: The wide public interest in data requires statistical scientists to become much more proactive in sharing their expertise.David Spiegelhalter,
Authors: Stephen Fienberg, Nancy Reid, Stephen Stigler
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2593358255