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Causal Analysis and Policy Assessment with
Bayesian Networks and BayesiaLab

A Free 2-Hour Workshop on Causality for Policy Analysts and Researchers
Monday, November 30, 15:00-17:00

The objective of this workshop is to provide a practical framework for better policy assessment and causal analysis. The proposed approach includes Directed Acyclic Graphs and Bayesian Networks. The techniques to be presented in this seminar can help address common challenges regarding causal inference from observational data.

This workshop is a "live" version of Chapter 10 in our new book, Bayesian Networks & BayesiaLab (download your free copy here).

Date and Location

November 30, 2015, 15:00 to 17:00
Academia - SGH Campus
Seminar Room L1-S1
20 College Rd
Singapore 169856

Workshop Overview

  • What is Policy Analysis?
  • Causal Inference by Experiment
  • Causal Inference from Observational Data plus Theory
  • Causal Effect Identification
    • Potential Outcomes Framework (Neyman-Rubin Model)
    • Using Directed Acyclic Graphs for Identification (e.g. Back-Door Criterion, etc.)
  • Computing the Effect Size Nonparametrically
    • Using Bayesian Networks and BayesiaLab for Effect Size Computation
      • Pearl's Graph Mutilation
      • Jouffe's Likelihood Matching
  • Managing Uncertainty Probabilistically with Bayesian Networks
    • Uncertain Evidence
    • Uncertainty about Policy Implementation (Probabilistic Intervention)
    • Using BayesiaLab for Optimization under Uncertainty 

Who should attend? 

Policy analysts, decision makers, policy consultants, applied researchers, statisticians, social scientists, data scientists, ecologists, epidemiologists, econometricians, economists, market researchers, knowledge managers, students and teachers in related fields.

About the Presenter

Stefan ConradyStefan Conrady has over 15 years of experience in decision analysis, market research, and product strategy with Fortune 100 companies in North America, Europe, and Asia. Today, in his role as Managing Partner of Bayesia USA and Bayesia Singapore, he is recognized as a thought leader in applying Bayesian networks for research, analytics, and reasoning. In this context, Stefan has recently co-authored a new book, Bayesian Networks & BayesiaLab - A Practical Introduction for Researchers.


Free Registration

Location & Map

Academia, 20 College Rd Singapore 169856

Please keep me posted about upcoming courses and events!