N Jacobsen
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    • N Jacobsen

      As for #10 I think it’s a misunderstanding in terminology of something called the central limit theorem: it states that any collection of identically distributed random variables will converge to a normal distribution (aka the bell curve). So, even though flipping a coin has a distribution of either heads or tails, if you flip a coin over and over and plot how many times out of each group of say, 100 flips, the coin lands heads or tails, the plot would approachment the normal distribution (that is, most of the time you’d get somewhere between 40 - 60 heads, but every now and then you might get 10 heads and 90 tails, and so on). What’s really remarkable about this is that it doesn’t just apply to a simple distribution like the coin toss, but to any distribution with finite mean and variance.