# Central limit theorem

In probability theory, the central limit theorem (CLT) states conditions under which the mean of a sufficiently large number of independent random variables, each with finite mean and variance, will be approximately normally distributed (Rice 1995). The central limit theorem also requires the random variables to be identically distributed, unless certain conditions are met. Since real-world quantities are often the balanced sum of many unobserved random events, this theorem provides a partial explanation for the prevalence of the normal probability distribution. The CLT also justifies the approximation of large-sample statistics to the normal distribution in controlled experiments.

— Wikipedia on Central limit theorem

2010.08.27 Friday ACHK

# Rebellion

.

Rebellion is almost as stupid as obedience. In either case you let yourself be defined by what they tell you to do. The best plan, I think, is to step onto an orthogonal vector. Don’t just do what they tell you, and don’t just refuse to. Instead treat school as a day job. As day jobs go, it’s pretty sweet. You’re done at 3 o’clock, and you can even work on your own stuff while you’re there.

— Paul Graham

.

.

.

2010.08.27 Friday $ACHK$

— Me@2010.08.27