The answer can be found in calculating uncertainty propagation. Uncertainty propagation is increase or decrease of input parameter uncertainty pictured over deterministic model on output values of model.
Figure 2: Picturing input parameter in statistical distribution shape in output value over a one dimensional model
If the model is more complicated, the uncertainty propagation cannot be solved directly, but using certain uncertainty estimation techniques. Some of them are: Monte Carlo, First Order Second Moment, Bayesian method or fuzzy set a cut method.
Figure 3: Uncertain input parameters and uncertain output parameters
