Sensitivity Analysis

Sensitivity analysis is a technique used to determine the effect of various values ​​of an independent variable on a particular dependent variable under a given hypothesis. This method is used for specific boundaries depending on one or more input variables, such as the effect of interest rate fluctuations on bond prices. Sensitivity analysis is a method of predicting the outcome of a decision if the situation is different from an important prediction. Sensitivity analysis is useful if the attempt to determine the actual result of a particular variable is different from the previous assumption.

There are various ways to measure and deal with risks. One way is to perform sensitivity analysis. Sensitivity analysis is a way to assign the uncertainty (value or otherwise) of the output of the model to the cause of the various uncertainties of the model input. The related method is uncertainty analysis. It focuses on quantifying the model output uncertainty. Ideally, uncertainty and sensitivity analysis should be performed at the same time. Another way is scenario analysis. This includes the process of analyzing potential future events by considering possible alternative outcomes.

Sensitivity analysis is used to examine changes in the structure of the organizational model. With the help of sensitivity analysis, anyone can determine the sensitivity of change based on the model value of the parameter. Using sensitivity analysis, you can easily evaluate and build models. Sensitivity analysis allows you to check the uncertainty associated with model parameters. When there is a difficult amount, it is difficult to calculate different parameters of the system dynamics model, and it is difficult to estimate the parameter value of the indeterminate model. Sensitivity analysis is an important tool for measuring the accuracy of parameters and it is necessary for the model to be effective and useful in actual scenarios. When we get the result that the sensitivity is not high with the help of the sensitivity analysis, we can estimate the likelihood in the model, but we can know the reasonable parameter value.

Sensitivity analysis is a way to test the sensitivity of a system or model variable by applying an incremental change. The system can be a physical or conceptual representation of the entire project or main elements and analyzes determine which variable has the greatest impact on the results, so the optimal setting or optimal solution It helps you choose. A technique for determining the influence of different values ​​of independent variables on a particular dependent variable under a given set of hypotheses. This method is used within a specific boundary depending on one or more input variables, such as the effect of interest rate fluctuations on bond prices.