• Nonparametric Bayesian Statistics

    Bayesian nonparametrics provides modeling solutions by replacing the finite-dimensional prior distributions of classical Bayesian analysis with infinite-dimensional stochastic processes.
  • Statistical and Computational Tradeoffs

    Computational limitations of statistical problems have largely been ignored or simply overcome by ad hoc relaxations techniques.
  • Four Lectures on Causality

    On May 10 and 11, Jonas Peters (University of Copenhagen) gave four lectures on causality. Slides and videos are available.

The Statistics and Data Science Center is an MIT-wide focal point for advancing research and education programs related to statistics and data science. The Center was created in 2015 with the goal of formalizing and consolidating efforts in statistics at MIT. The Center’s academic mission is to host and develop new academic programs, from a minor to a PhD in statistics and data science.



Photo of Esther Duflo
MIT News | July 06, 2017

Study: Preschoolers learn from math games — to a point

A study co-authored by Professor Esther Duflo finds games for pre-schoolers can improve conceptual math skills, however, the gains may not carry ...

MIT News | June 29, 2017

Investigating the trap of unemployment

PhD student Aicha Ben Dhia studies France’s labor market from the perspective of local job-seekers.

MIT News | June 08, 2017

QS ranks MIT the world’s No. 1 university for 2017-18

Ranked at the top for the sixth straight year, the Institute also places first in 12 of 46 disciplines.