Coursera - A Crash Course in Causality Inferring Causal Effects from Observational Data by Univer...

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Coursera - A Crash Course in Causality Inferring Causal Effects from Observational Data by University of Pennsylvania
Video: .mp4 (1280x720) | Audio: AAC, 44100 kHz, 2ch | Size: 1.36 Gb
Genre: eLearning Video | Duration: 10h 49m | Language: English

We have all heard the phrase "correlation does not equal causation."  What, then, does equal causation?  This course aims to answer that question and more!  Over a period of 5 weeks, you will learn how causal effects are defined, what assumptions about your data and models are necessary, and how to implement and interpret some popular statistical methods.

At the end of the course, learners should be able to:
1.  Define causal effects using potential outcomes
2.  Describe the difference between association and causation
3.  Express assumptions with causal graphs
4.  Implement several types of causal inference methods (e.g. matching, instrumental variables, inverse probability of treatment weighting)
5.  Identify which causal assumptions are necessary for each type of statistical method

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