In simulations, what do randomly generated inputs represent?

In simulations, what do randomly generated inputs represent?

• A. A value drawn from a probability distribution
• B. A constant historical number
• C. The average of past forecasts
• D. The maximum demand scenario

Answer: (A)

Uncertain inputs in simulations are modeled as random draws from probability distributions. In a Monte Carlo model, you specify for each uncertain input a distribution that reflects what you know about its range and likelihoods. For each run, the model draws a value from those distributions and uses it to compute outcomes. Repeating many times builds an empirical distribution of results, showing the range of possible outcomes and their probabilities. This captures uncertainty rather than fixing a single number. A constant historical value would ignore variability, the average of past forecasts is just a summary statistic, and a maximum demand scenario is a single extreme case, not the distribution of possible inputs.

Uncertain inputs in simulations are modeled as random draws from probability distributions. In a Monte Carlo model, you specify for each uncertain input a distribution that reflects what you know about its range and likelihoods. For each run, the model draws a value from those distributions and uses it to compute outcomes. Repeating many times builds an empirical distribution of results, showing the range of possible outcomes and their probabilities.

This captures uncertainty rather than fixing a single number. A constant historical value would ignore variability, the average of past forecasts is just a summary statistic, and a maximum demand scenario is a single extreme case, not the distribution of possible inputs.