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How to analyze conditional field resolution

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great so lets jump into conditional outcome modeling here is the adjustment formula for the average treatment effect thats hopefully reasonably familiar to you by now so on the left hand side we have a causal s demand and on the right hand side we have a statistical s demand and we want to turn this statistical s demand into an actual estimate we want an estimator that can take in data and then give us that estimate so theres two things well need to do here the first is to model these conditional expectations here we can use any statistical model that models this conditional expectation so if youve used scikit-learn before you can pretty much just take anything out of scikit-learn and plug it in to model this conditional expectation assuming that its minimizing the mean squared error of the true ys and the predicted ys given treatment and w so you can even use fancy models like deep neural networks to model this conditional expectation what im going to do now is rewrite this

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