Monte Carlo Simulation
Version 1.0.0 · Updated 2026-07-30
CORE DEFINITION
When a system is too complex to be calculated with formulas, a computer performs thousands of random experiments (simulating various possible input combinations) to derive the probability distribution of the results.
SCAFFOLDING EFFECT
Reduce cognitive load
- Brute-force solving: When facing uncertainty (such as project duration or investment returns), do not give an 'average' but run a simulation to conclude 'there is a 90% probability of completion within 30 days, and a 10% probability of delay to 50 days.' This is the most honest calculation of luck.
Anchor fast decisions
Estimate numerical results of complex systems or mathematical integrals through a large number of random samples. Use frequency to approximate probability, handling uncertainty that is analytically intractable.
MINIMUM ACTION
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Monte_Carlo_methodverified
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