About this Event
Why does a treatment work? Does a policy actually improve outcomes? Answering these questions requires moving beyond correlation to causation and doing so with statistical rigor. This short course provides an accessible introduction to causal inference and the semiparametric ideas that power modern causal analysis, culminating in the increasingly popular framework of double machine learning. The course is designed for statisticians, data scientists, and quantitative researchers who want to understand how causal effects can be estimated reliably, especially when flexible machine learning methods are used to handle complex data. No prior background in causal inference or semiparametric theory is assumed, but some basic knowledge of mathematical statistics would be of help.
Event Venue & Nearby Stays
Tallgrall Ballroom (the 2nd floor), Kramer Dining Center, 1835 Claflin Road, Manhattan, United States
USD 30.00 to USD 75.00
