Central Limit

Definition

Considered the most fundamental theory in modern statistics.

If you a sample of random variables and average it, do it multiple times, it should look like a Normal Distribution.

This is important because we can then use statistical tests that assumes normality even when the underlying data is not normal but the sample size is large enough.

Though this fails with Heavy tail

But how much samples?

1. Roughly symmetric? 15-30
2. Heavily skewed? 50 or more
3. Really, really skewed? 100 or more

Though this wisdom seems to be just parotted.