There are many phenomena in everyday life where it’s very difficult to model the problem. There are so many variables and so many dependencies that any approximation or assumption would lead to a huge errors in outputs. This is usually a combination of uncertainty and variability. Even though we have access to all the historical information, we can’t accurately predict a future outcome because of inaccurate modeling. This becomes especially relevant when we are dealing with systems where the degrees of freedom are dependent on each other. An example would be movement of fluids or kinetic modeling of gases. How do we compute the possible outcomes? How can we assess the impact of all the free variables to make sure we predict the outcome under uncertainty? Continue reading

# What Is Monte Carlo Simulation

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