Run the simulation on known results, to validate that the results are the ones that we’d expect. A wrong result proves the simualtion is wrong. A right result does not prove the simulation is correct but helps in being hopeful about it.

Incremental changes to simulations can help answer different questions. But it’s important to understand what’s right about the first simulation.

When simulations close in on a number, with decreasing standard deviations, we don’t know for sure about the statistical true value, but instead about what our simulation can infer only. A wrong simluation will still give good results, but the value might be wrong. It is why it’s important to do a sanity check.