This cross-disciplinary seminar series will feature speakers tackling social science questions with big data and cutting-edge computation, data analysis, and inference techniques. Talks will alternate between Berkeley and Stanford, and logistics will be arranged for people from both institutions to see every talk.
The following topics will be emphasized:
1. What every student should know about causal inference, and why it is not taught in Statistics 101
2. The Mediation Formula, and what it tells us about "How nature works"
3. What mathematics can tell us about "external validity" or "generalizing across populations"
4. What population data can tell us about unsuspected heterogeneity
5. What causal analysis tells us about recovery from missing data
A light lunch will be provided.
