For Friday November 10 lecture: Read and blog about Section 6.3

Difficult:

Basically this whole section. If I understand it right, it's saying that, given any random distribution, I can sum several random variables from that distribution, and eventually the probability of those events all happening converges to the normal distribution. But I'm not sure quite how, or why. I can see what was done but not really follow it.

Application:

I think that the central limit thm is used in a lot of practical applications- like they said, they expect grades, snowfalls, etc, though I rather like the example they give of rolling dice.

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