Intro to Stan Software for Bayesian Analysis with Ben Goodrich

Zalando would love to welcome Ben Goodrich (https://sipa.columbia.edu/faculty/ben-goodrich), whose primary research area at Columbia's School of International and Public Affairs (SIPA) is quantitative analysis with a focus on developing algorithms to understand social and political problems.

Presentation: An Introduction to the Stan Software for Bayesian Analysis

The Stan project implements a probabilistic programming language, a library of mathematical and statistical functions, and a variety of algorithms to estimate statistical models in order to make Bayesian inferences from data. This talk will provide a brief introduction to modern Bayesian inference using Hamiltonian Markov Chain Monte Carlo (MCMC) as implemented in Stan.

About the Speaker:

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Ben Goodrich is a core instructor in the Quantitative Methods in the Social Sciences Master's Program at Columbia University, where he teaches Missing Data, Bayesian Statistics, Data Mining, Data Analysis, and Theory and Methodology. He is also a core developer of the statistical software Stan and the maintainer of two R packages that interface with Stan. Ben received his Ph.D. in Government and Social Policy from Harvard University in 2010.

Please do not forget to bring your ID and update your reservation if you cannot make it.