Causality

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Presented by: Professor Marloes Maathuis - ETH Zurich
Causal questions are fundamental in all parts of science. Answering such questions from non-experimental data is notoriously difficult, but there has been a lot of recent interest and progress in this field. I will discuss current approaches to this problem and outline their potential as well as their limitations. The concepts and methods will be illustrated by several examples.
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20:10 +1 co-variate adj & the table 2 fallacy in multi reg

JCResDoc
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This is exactly Judea Pearl's brilliant idea, that he discusses in his latest book "The Book of Why".

TernaryM
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17:10 v(x) in model - common err in multi regrn

JCResDoc
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22:22 co-variate adj interpretation err eg 2

JCResDoc
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19:20 non confounding path unexpected bias

JCResDoc
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33:44 guess the DAG (outside in IntiEst)

JCResDoc
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i wish i could regress the 10 dollars in my wallet on the last 4days of life to see where this wks paycheck went.

JCResDoc