Developing a Statistics Curriculum for the Data Revolution

• Activity Number: 153
• Type: Invited
• Date/Time: Monday, August 4, 2014 : 10:30 AM to 12:20 PM
• Sponsor: ASA
• Author(s): Deepak Agarwal*+ and William S. Cleveland*+ and Ryan Hafen*+ and Mark Hansen*+
• Companies: LinkedIn and Purdue University and Pacific Northwest National Laboratory and Columbia University

Abstract

Big Data and data science present both challenges and opportunities for statisticians. The promise of Big Data for transforming business, science, and government has been proclaimed widely. Data science is an emerging field often connected to Big Data, described as an amalgam of computer science, mathematics, data visualization, machine learning, distributed data management - and statistics. Ideally, the opportunities for statisticians should be enormous. However, the scope of Big Data and data science transcends traditional statistics, as new data management and computational paradigms and new analytical and visualization techniques are required. Of considerable importance is training the next generation of statisticians in the skills to make immediate contributions to data science. In the June 2013 Amstat News, 2012, 2013, and 2014 ASA presidents Bob Rodriguez, Marie Davidian, and Nat Schenker announced formation of an ASA workgroup whose charge is to study graduate-level curriculum development in statistics programs to equip students with the knowledge needed. This panel will present the report of the workgroup and serve as a forum for discussion.