Monte Carlo analysis
In: Mathematics
Monte Carlo is really a catch-all term for any simulation/analysis that involves doing things a large number of times using random numbers as a starting point.
For example, let’s say you want to predict a horse race. The classic approach might be to try to determine exactly how fast each horse will run based on its muscle mass, build, diet, jockey, prior performance etc. then pick the fastest horse as the winner.
A monte Carlo approach will involve figuring out a rough range of speeds for each horse (e.g. between 15-20mph) and then using a random number generator to pick a speed in that range. You then simulate the race and see who wins. You repeat this process 100000 times and find out that horse number 3 wins 70% of the time, horse 2 only wins 2% of the time etc etc.
This was probably a bad example, but basically Monte Carlo is useful when the variables of a problem are far too numerous or fluctuate too much to predict accurately.
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