Welcome to STAT250! This seminar is limited enrollment, and will only be offered once; please fill out this survey by Friday, September 6, if you are interested in joining! We will accept late submissions on a case by case basis.


Data science combines data, statistical thinking, and computation to gain insights and make inferences and predictions. This seminar will focus on effective strategies for teaching data science. To do this, students will participate in designing a new introductory data science course that takes a holistic approach to the data science process, helping students understand the key factors involved, from data collection and exploratory data analysis to modeling, evaluation, and communication of results. Participants in the seminar will also learn data science concepts through developing and evaluating data science case studies.

Instructors

  • Joseph Blitzstein (Professor of the Practice in Statistics in the Department of Statistics at Harvard University)
  • Allen Downey (Visiting Professor in Computer Science in the School of Engineering and Applied Sciences at Harvard University)
  • Hanspeter Pfister (An Wang Professor of Computer Science in the School of Engineering and Applied Sciences at Harvard University)
  • Xiao-Li Meng (Whipple V. N. Jones Professor of Statistics in the Department of Statistics at Harvard University)
  • Liberty Vittert (Visiting Assistant Professor in in the Department of Statistics at Harvard University)

Course Sessions

Lectures: Mondays, 3:00-5:30pm, Science Center 706.

First Class: Monday, September 9, 2019.

Office Hours: Office hours will be posted on Canvas

Lecture Resources: Discussion forum on Piazza. Materials and grades on Canvas

Teaching Fellows

TBD