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Wednesday, November 26, 2014

Causality for Policy Assessment and Impact Analysis

From BayesiaLab.     Nicely done live recorded lecture.  To get the full extensive tutorial you need to register.  The video is open without registration.

New Video Lecture: Causality for Policy Assessment and Impact Analysis
Presenters: Stefan Conrady and Dr. Lionel Jouffe
Recorded on November 18, 2014, at George Mason University Arlington Campus.
Runtime: 01:52:24

The objective of this presentation is to provide a practical framework for causal effect estimation with non-experimental data. We will present a range of methods, including Directed Acyclic Graphs and Bayesian networks, which can help distinguish causation from association when working with data from observational studies. The presentation revolves around a seemingly trivial example, Simpson’s Paradox, which turns out to be rather tricky to interpret in practice.

This talk is a "live" version of a recent tutorial, Causality for Policy Assessment and Impact Analysis - Directed Acyclic Graphs and Bayesian Networks for Causal Identification and Estimation. .... " 

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