Precision analysis
Simulations and Monte Carlo methods
Article REF: AF600 V1
Precision analysis
Simulations and Monte Carlo methods

Authors : Gerardo RUBINO, Bruno TUFFIN

Publication date: October 10, 2007, Review date: November 19, 2019 | Lire en français

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3. Precision analysis

Monte Carlo methods are approximate methods for calculating a value. As with any method of this kind, it is important to have tools that allow us to know the accuracy obtained. Since Monte Carlo methods use random variables, statistical tools are used [6].

3.1 Confidence intervals

Statistical tools can be used to obtain a confidence interval, i.e. an interval of the form ]x 1,n (α), x 2,n (α)[ where n is the sample size, meaning that the value x sought is within this interval with probability α. Increasing the confidence level α (decreasing the risk 1 - α) leads to increasing the interval size for a given sample size n.

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