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#causality #statistics
Causal graphs are special in that we additionally assume that the edges have causal meaning (causal edges assumption, Assumption 3.3). This assumption is what introduces causality into our models, and it makes one type of path take on a whole new meaning: directed paths. This assumption endows directed paths with the unique role of carrying causation along them. Additionally, this assumption is asymmetric; “ 𝑋 is a cause of 𝑌 ” is not the same as saying “ 𝑌 is a cause of 𝑋 .” This means that there is an important difference between association and causation: association is symmetric, whereas causation is asymmetric
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owner: crocodile - (no access) - Introduction_to_Causal_Inference-Nov19_2020-Neal.pdf, p39


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