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Explore the fundamentals of causal inference in this 49-minute conference talk by Eyal Kazin, Staff Data Scientist at Babylon. Learn how to uncover causal relationships within observational data without resorting to expensive randomized control trials. Discover the importance of asking "Why?" to extract deeper insights from your data and avoid common misinterpretation pitfalls like Simpson's Paradox. Gain practical knowledge on conducting better experiments and making more informed data-driven decisions. Access additional resources, including presentation slides and a Simpson's Calculator app, to further enhance your understanding of causal inference concepts.
Syllabus
Introduction to Causal Inference
Taught by
Data Science Festival