6 Central limit theorem
Central limit theorem
The CLT states that when the number of random variables in a sample size is sufficiently large it can be approximated by the normal (Gaussian) distribution.
This is useful in risk assessment because the errors in measured parameters can be assumed as a normal distribution, without having to do additional analysis to actually prove that.