#221: Causal Inference Revisited (...DAGnabbit!) with DJ Rich - a podcast by Michael Helbling, Tim Wilson, and Moe Kiss

What causes us to keep returning to the topic of causal inference on this show? DAG if we know! Whether or not you're familiar with directed acyclic graphs (or… DAGs) in the context of causal inference, this episode is likely for you! DJ Rich, a data scientist at Lyft, joined us to discuss causality — why it matters, why it's tricky, and what happens when you tackle causally modelling the complexity of a large-scale, two-sided market! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

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