## what if what???

*[Here is a section of the Wikipedia page on Monte Carlo methods which makes little sense to me. What if it was not part of this page?!]*

## Monte Carlo simulation versus “what if” scenarios

There are ways of using probabilities that are definitely not Monte Carlo simulations – for example, deterministic modeling using single-point estimates. Each uncertain variable within a model is assigned a “best guess” estimate. Scenarios (such as best, worst, or most likely case) for each input variable are chosen and the results recorded.

^{[55]}By contrast, Monte Carlo simulations sample from a probability distribution for each variable to produce hundreds or thousands of possible outcomes. The results are analyzed to get probabilities of different outcomes occurring.

^{[56]}For example, a comparison of a spreadsheet cost construction model run using traditional “what if” scenarios, and then running the comparison again with Monte Carlo simulation and triangular probability distributions shows that the Monte Carlo analysis has a narrower range than the “what if” analysis. This is because the “what if” analysis gives equal weight to all scenarios (see quantifying uncertainty in corporate finance), while the Monte Carlo method hardly samples in the very low probability regions. The samples in such regions are called “rare events”.

October 7, 2019 at 8:32 am

The section makes some sort of sense to me and has some utility but is lacking in a reference to exactly what they mean by “what if” scenarios. It seems they are saying some business processes are effectively doing importance sampling with all importance weights identical and that’s bad practice! I’d recommend having this discussion on the Wikipedia talk page https://en.wikipedia.org/wiki/Talk:Monte_Carlo_method as that’s the Wikipedia way to do things.