<img height="1" width="1" alt="" style="display:none" src="https://www.facebook.com/tr?id=648880075207035&amp;ev=NoScript">

Causal Identification & Estimation Workshop in Singapore


Forget Big Data, the true frontier in the field of analytics is causal inference! Today, Stefan Conrady hosted a workshop at Academia in Singapore on this very topic: causal identification and estimation with Directed Acyclic Graphs and Bayesian Networks. The infamous Simpson's Paradox example highlights how easy it is to make catastrophic errors in computing causal effects. If you couldn't make it to this workshop today, take a look at Chapter 10 in our new book, Bayesian Networks & BayesiaLab, which discusses this topic in detail.