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Review:

Monte Carlo Simulation

overall review score: 4.5
score is between 0 and 5
Monte Carlo simulation is a computational technique used to model the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables.

Key Features

  • Uses random sampling to model uncertainty
  • Can be used in various fields, including finance, physics, and engineering
  • Provides a range of possible outcomes instead of a single prediction

Pros

  • Great for analyzing complex systems with many variables
  • Allows for the incorporation of uncertainty in predictions
  • Provides a visual representation of possible outcomes

Cons

  • Requires a large number of iterations to produce accurate results
  • Can be time-consuming and computationally intensive
  • Assumes that all variables are independent, which may not always be the case

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Last updated: Wed, Feb 28, 2024, 06:10:08 PM UTC