# Better Estimation of the Expected Value

In this lesson, we will try to find a better estimate of the expected value in the continuous case.

In the previous lesson, we showed why our naïve implementation of computing the expected value could be fatally flawed: there could be a “black swan” region where the “profit” function `f`

is different enough to make a big difference in the average, but the region is just small enough to be missed sometimes when we’re sampling from our distribution `p`

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