The Law of Total Expectation states that the expected value of a random variable can be calculated by taking the weighted average of its conditional expectations given a partition of the sample space. This concept connects various parts of probability theory, particularly linking to how we approach understanding probabilities through conditioning, expectations, and transformations of random variables.
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