The Bayesian Bootstrap

CAUSAL DATA SCIENCE

A short guide to a simple and powerful alternative to the bootstrap

In causal inference we do not want just to compute treatment effects, we also want to do inference (duh!). In some cases, it’s very easy to compute the (asymptotic) distribution of an estimator, thanks to the central limit theorem. This is the case when computing the average treatment effect in AB tests or randomized controlled trials, for …

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