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Causal inference when you can't experiment: difference-in-differences and synthetic controls

Causal inference when you can't experiment: difference-in-differences and synthetic controls

FromLinear Digressions


Causal inference when you can't experiment: difference-in-differences and synthetic controls

FromLinear Digressions

ratings:
Length:
21 minutes
Released:
Mar 9, 2020
Format:
Podcast episode

Description

When you need to untangle cause and effect, but you can’t run an experiment, it’s time to get creative. This episode covers difference in differences and synthetic controls, two observational causal inference techniques that researchers have used to understand causality in complex real-world situations.
Released:
Mar 9, 2020
Format:
Podcast episode

Titles in the series (100)

Linear Digressions is a podcast about machine learning and data science. Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago.