Please join the Statistical Computing Workshop as they host Andrés Cruz is a PhD candidate in Government at UT Austin.
Abstract: R is the de facto programming language in quantitative social science. Yet many developments in statistical computing and machine learning hit Python first. In this tutorial, we will cover how to seamlessly integrate bits of Python into our R workflows, via the reticulate package. In particular, we will study JAX, a Python library for high-performance computing that provides a number of useful features, including automatic differentiation, automatic vectorization, and just-in-time compilation. We will apply these tools to concrete political science tasks, such as measurement error propagation and sensitivity analysis.
Bio: Andrés Cruz is a PhD candidate in Government at UT Austin, where he also obtained an MS in Statistics. He is a political methodologist developing tools for robustness and sensitivity analysis, with applications to topics such as the cross-national study of democracy and comparative constitutionalism. Before coming to UT, Andrés received a BA and MA in Political Science from Pontificia Universidad Católica de Chile.
The Statistical Computing Workshop (formerly R Workshop) is a year-long series that meets three times per quarter during the academic year. The purpose of the workshop is to learn, practice, and update cutting edge statistical programming skills as they apply to quantitative and computational social science.
Workshop meetings will feature internal or external speakers introducing a new tool, method, or research project involving statistical computing in the broadest sense. All meetings are hybrid or fully virtual.
Ariel Sowers
(847) 491-7454
Email