Session 651: Thu, 8/2/2018, 10:30 AM - 12:20 PM CC-West 203
(https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/ActivityDetails.cfm?SessionID=215338)
Sponsors:
- Section on Statistical Education
- Section on Statistical Learning and Data Science
- Section on Statistical Computing
Organizer & Chair: Ben Baumer, Smith College
- 10:35 AM Dismantling Math, Stats, and CS Silos: PCMI Guidelines for Undergraduate Majors in Data Science
- Albert Y. Kim, Smith College
- 10:50 AM Pathways Through the Major in Statistical and Data Science at Smith
- Randi L. Garcia, Smith College
- 11:05 AM Herding Cats: Pros and Cons of a Large-Team Approach to Data Science at a Major Research University
- David Hunter, Penn State University
- 11:20 AM Designing a Group Major in Data Science
- Deborah Nolan, University of California, Berkeley
- 11:35 AM Discussant:
- Joseph Blitzstein, Harvard University
- 11:50 AM Discussant:
- Mine Cetinkaya-Rundel, Duke University
- 12:05 PM Floor Discussion
Description: In “50 Years of Data Science”, David Donoho relates that “John Chambers and Bill Cleveland each envisioned a would-be field that is considerably larger than the consensus Data Science Master’s...but at the same time more intellectually productive and lasting. The larger vision posits a professional on a quest to extract information from data.” As more schools add undergraduate majors in data science, we explore what these programs entail, how they differ from existing majors in statistics (and computer science), and whether they fulfill Donoho’s vision for “Greater Data Science.”