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What is Law of Iterated Expectations Explained about?
1. The law of iterated expectations states that the expected value of a random variable Y can be written as the expected value of the expected value of Y conditioned on another random variable X. This forms the foundation for important results in applied statistics. 2. Examples of how the law of iterated expectations applies include showing that the mean of sampled data matches the mean when data is grouped and averaged, defining martingales, and proving the propensity score theorem which reduces dimensiona
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- emiliortiz1
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- EN