Sensitivity testing is the process of changing your assumptions about the value of Constants in the model and examining the resulting output. Manual sensitivity testing involves changing the value of a Constant (or several Constants at once) and simulating, then changing the value of the Constant again and simulating again, and repeating this action many times to get a spread of output values.
Monte Carlo simulation, also known as multivariate sensitivity simulation (MVSS), makes this procedure automatic. Hundreds or even thousands of simulations can be performed, with Constants sampled over a range of values, and output stored for later analysis. Latin Hypercube sampling is a specialized form of sensitivity testing that allows faster sensitivity testing on very large models.
