Andrew Gelman

What are the most important statistical ideas of the past 50 years?

Andrew Gelman
Higgins Professor of Statistics and Professor of Political Science
Columbia University

Venue: virtual

Abstract:

We argue that the most important statistical ideas of the past half century are: counterfactual causal inference, bootstrapping and simulation-based inference, overparameterized models and regularization, multilevel models, generic computation algorithms, adaptive decision analysis, robust inference, and exploratory data analysis. We discuss common features of these ideas, how they relate to modern computing and big data, and how they might be developed and extended in future decades. The goal of this talk is to provoke thought and discussion regarding the larger themes of research in statistics and data science.