Using the definitions found in Chapter 1 of Quantitative Analysis, the Internet, and your own personal experiences, make notes on and post one example of each of the following to the class Discussion Board topic “Deterministic and Probabilistic Models”.
A deterministic model;
A probabilistic model; and
A situation in which you could use post optimality analysis (also known as sensitivity analysis).
A probabilistic model is one in which the output is not completely determined by the inputs, but is instead a function of some underlying probability distribution. An example of this would be a model that predicts the future path of a projectile based on its initial velocity and angle of launch, but also takes into account the fact that there is some uncertainty in these inputs.
A situation in which post optimality analysis could be used is if you have a mathematical model that predicts the future path of a projectile, but you are not sure of the exact values of the inputs (velocity and angle of launch). By using post optimality analysis, you can vary the inputs and see how sensitive the output is to these changes. This can help you to determine the most likely values of the inputs, and hence the most likely path of the projectile.
