Causal effects measure how actions change the world
Does this drug improve survival? Does portfolio diversification boost profit? Do social influencers actually influence anybody? These are causal questions, because they ask about the relative merit of one choice over another. Mere prediction cannot answer causal questions because it just extrapolates from the current state of affairs. By contrast, causality asks what would happen if business as usual were disrupted by intervention.
DAGs to the rescue
Big Data Ignite is pleased to announce confirmation of a full-day workshop “Understanding Causality to Advance from Prediction to Action” led by Felix Elwert (University of Wisconsin). This workshop (and several others) will be held on Wednesday, September 19 as part of this year’s Big Data Ignite 2018.
Dr. Elwert’s workshop will introduce a powerful graphical approach (using directed acyclic graphs, or DAGs), developed by Turing Award winner Judea Pearl (author of the recently published The Book of Why) and others. By the end of the day, workshop participants will be able to
- recognize causal questions,
- determine what data are needed to answer them, and
- avoid common mistakes in causal reasoning.
The workshop should be accessible to anyone who has had a first course in statistics and some prior exposure to regression. (No calculus or any particular programming language are required.)
Dr. Elwert is the Romnes Professor of Sociology and Biostatistics and Medical Informatics at the University of Wisconsin-Madison. He is a Harvard-trained specialist in causal inference and winner of many prizes, including the first Causality in Statistics Education Award from the American Statistical Association (2013) for his innovative two-day course, Causal Inference with Directed Acyclic Graphs. His methodological research translates between computer science, statistics, and the social sciences; and his applied research deals with social inequality, education, and public health. His research has appeared the American Journal of Public Health, the American Journal of Sociology, Demography, and Biometrics. He is also a highly regarded instructor who regularly teaches courses on causal inference to academics and business professionals around the globe.