CAUSAL INFERENCE: POTENTIAL OUTCOMES AND CONFOUNDERS скачать в хорошем качестве

CAUSAL INFERENCE: POTENTIAL OUTCOMES AND CONFOUNDERS

In this video, we introduce core concepts in causal inference—the task of determining whether a treatment, such as a medication, has a genuine causal effect on an outcome like patient recovery. We begin by introducing potential outcomes, which provide a formal framework for defining causal effects. Using this framework, we show that observed associations do not always reflect true causality, and explain how randomized treatment assignment can address this issue. We then introduce confounding factors—variables that can distort observed effects—and explain how we can correct for their influence under certain assumptions. Probability and statistics book: https://a.co/d/7k259eb Website with free preprint, videos, slides and solutions to exercises: https://www.ps4ds.net Slides for this video: https://github.com/cfgranda/ps4ds/blo...