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.

Central limit theorem sample code

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Risk Assessment Copyright © 2015 by R.A. Borrelli is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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