Sensitivity Model: The Concept Of Sensitivity Analysis Model

The idea of Sensitivity analysis in any robustness studies is key element in structuring and solving decision models. It has been long identified as a key stage in the modelling, inference and evaluation used in the field of operational studies and research as well as decision analytics and risk management studies. The core questions that sensitivity analysis is trying to answer to is "what makes the most difference in this decision? In another word, what is the most important element that makes a decision logical?

The widely used definition of sensitivity analysis relates to the variation of input variables to a model to investigate the impact on the output variables. The use of mathematical modelling and statistical inference combined with operational research decision analysis is key requirement. In today's professional analyst work would not be complete without the use of sensitivity analysis, although

Figure 2 explains the different processes and steps that are super imposed on the Bayesian model with many steps to explain the relations. Figure 2: Sensitivity Analysis model [1].

To explain figure 2, the following are the keys for the letters in the model:
A. To build and explore consequence models.
B. To explore the relationship between science and consequence models
C. To support the elicitation of judge. Mental inputs to an analysis.
D. To develop efficient computational algorithms.
E. To design experiments.
F. To guide the making of inferences, forecasts and decisions.
G. To explore mid build consensus.
H. To build understanding.
For the purpose of this study, and due to the limited scope, we are not going to explain in details the above steps. Though in the literature, it has been discussed and explained in great depth.
3 .0 RELATION BETWEEN STOCKHOLDERS AND SENSITIVITY ANALYSIS