Joseph Blitzstein

Joe Blitzstein is Professor of the Practice in Statistics at Harvard University, where has taught since 2006, after completing his Ph.D. in Mathematics (with a masters in Statistics) at Stanford University, advised by Persi Diaconis. He is originally from Los Angeles, California, and did his undergraduate studies in Mathematics at the California Institute of Technology. At Harvard, he has taught a wide range of undergraduate and graduate probability and statistics courses, including the popular statistics class Stat 110, which provides a comprehensive introduction to probability as a language and framework that can be applied wherever there is data, randomness, or uncertainty. Stat 110 has grown to over 500 on campus students per year at Harvard. With Professor Hanspeter Pfister from Computer Science, Joe also launched Harvard's first course in data science in 2013. Joe’s main research interests are in statistical inference for networks, “big data”, and other complex data structures. Joe is also a chess expert, and serves as faculty adviser to the Harvard Chess Club.

Self Paced

Course Auditing

EdX

Harvard University

HarvardX

Categories

Statistics & Data Analysis

Effort

Languages

Learn probability, an essential language and set of tools for understanding data, randomness, and uncertainty. Probability and statistics help to bring logic to a world replete with randomness and uncertainty. This course will give you tools needed to understand data, science, philosophy, engineering, economics, and finance. [...]

Central Limit Theorem

Self Paced