Σεμινάριο

Πάνος Τούλης, Assistant Professor of Econometrics and Statistics, University of Chicago, Booth School of Business

"PART A: Causal inference in statistics and econometrics/ PART B: Research Opportunities for Statistics Graduates in the University of Chicago"

ΔΕΥΤΕΡΑ 12/12/2016, 15:00
Κτίριο Μεταπτυχιακών Σπουδών, Ευελπίδων και Λευκάδος, αίθουσα 607, 6ος όροφος

Περίληψη A μέρους (στα αγγλικά)

Causal inference in statistics and econometrics

Causality is one of the most hotly debated and yet elusive concepts in the history of human thought. During the past few decades we have witnessed significant advances in how we understand and infer causality in statistics and econometrics, originating from the pioneering works in experimental design by R.A. Fisher and J. Neyman. In this talk we will make a quick review of such advances. We will then discuss some crucial shortcomings of current causal inference methods, especially those related to applications in complex systems, such as social networks or dynamic economies. This suggests that new causal inference methods will need to creatively combine appropriate mathematical tools to model such complexity.  

Περίληψη Β μέρους (στα αγγλικά)

Research Opportunities for Statistics Graduates in the University of Chicago

We will discuss opportunities for graduate studies in the University of Chicago, including the Econometrics & Statistics group at the Booth Business School and the Department of Statistics.

Our discussion will cover several aspects of the PhD program, such as research areas, faculty, funding, and everyday life.