sensitivityanalyse

Sensitivity analysis is a technique used in various fields, including engineering, economics, and environmental science, to determine how different values of an independent variable impact a particular dependent variable under a given set of assumptions. It is a crucial tool for understanding the robustness of a model or system and for identifying the most influential factors.

The primary goal of sensitivity analysis is to assess how the uncertainty in the output of a model can be apportioned to different sources of uncertainty in the model input. This is achieved by systematically varying the input parameters and observing the corresponding changes in the output. The results of a sensitivity analysis can help in identifying which inputs have the most significant impact on the output, allowing for targeted efforts to reduce uncertainty or improve model accuracy.

There are several methods for conducting sensitivity analysis, including local sensitivity analysis, global sensitivity analysis, and screening methods. Local sensitivity analysis examines the sensitivity of the output to small changes in the input parameters around a specific point. Global sensitivity analysis, on the other hand, considers the entire range of possible input values and their effects on the output. Screening methods are used to quickly identify the most influential inputs without requiring extensive computational resources.

Sensitivity analysis is widely used in risk assessment, decision-making, and optimization processes. It provides valuable insights into the behavior of complex systems and helps in making informed decisions under uncertainty. By understanding the sensitivity of a system to different inputs, stakeholders can prioritize resources and efforts to improve model accuracy and reliability.