A Primer on Causal Analysis

2018/06/05 by Finnian Lattimore, Lattimore, Finnian, Cheng Soon Ong +1
Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.AI #cs.LG #stat.ML

paper · pdf · doi:10.48550/arxiv.1806.01488

Parts of this document are copied verbatim from Finnian Lattimore's PhD thesis, ANU 2018

arxiv created 2018/06/05 · arxiv updated 2018/06/06

Abstract

We provide a conceptual map to navigate causal analysis problems. Focusing on the case of discrete random variables, we consider the case of causal effect estimation from observational data. The presented approaches apply also to continuous variables, but the issue of estimation becomes more complex. We then introduce the four schools of thought for causal analysis

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