The process in which a model is run many times with different combinations of low and high values of each experimental parameter to help account for uncertainty in parameter values is called
A) sensitivity analysis.
B) iterative digression.
C) risk assessment.
D) scenario building.
E) modeling.

Question

Quizplus · Accepted Answer

Sensitivity analysis involves running a model multiple times with varying parameter values to understand how changes in these parameters affect the model's outcomes, thereby accounting for uncertainty.

The Process in Which a Model Is Run Many Times