Monte Carlo Simulations

Monte Carlo Simulations

Guesstimate uses Monte Carlo (opens in a new tab) techniques to produce our results. The Monte Carlo method involves repeatedly sampling the underlying probability distributions of a random variable and performing all calculations involving that random variable many times, with those sampled values. The Monte Carlo method is a brute force, random process of approximating the true, resulting distribution.

For example, if you wanted to compute the value of X×YX \times Y, where XX and YY are random variables (such as Guesstimate cells whose inputs are ranges, or data streams), then using the Monte Carlo method you would compute many sample values for XX and many sample values for YY, then multiply those samples together pairwise to produce the output distribution for X×YX \times Y.

Within Guesstimate, 5000 samples are performed per stochastic expression. 5000 is enough to be useful for most estimates, but not enough to slow the system down. In the future, this amount may be variable depending on the need and circumstances.