This is going to be a monthly series. I can't remember where I saw the link that caused me to print this out. Anyway, it's an educational piece that explains sampling and the Central Limit Theorem. It requires little knowledge of mathematics. But there are lots and lots of educational pieces that make the same point so not important to read this one specifically. I found the first column relatively dense and not really important. I think I only really fully accepted the Central Limit Theorem when I played around with a tool online that automatically did distributions of the mean for all sorts of weird samples. It is a little counter-intuitive that when one samples from all sorts of distributions e.g. heavily skewed ones, that the distribution of the sample means tends towards being normally distributed (i.e. a nice bell shaped curve esp. when the samples removed are not small). The implications of this are used a lot in statistics.