tundlikkusanalyüsi

Tundlikkusanalyüsi, also known as sensitivity analysis, is a technique used in various fields, including mathematics, statistics, engineering, and economics, to determine how the uncertainty or variability in the output of a mathematical model or system can be attributed to different sources of variation in the input. In essence, it aims to understand which input factors have the most significant impact on the model's results.

The process typically involves systematically varying one or more input parameters of the model and observing the resulting changes in the output. This can be done through various methods, ranging from simple one-at-a-time variations to more sophisticated global techniques that consider the interactions between multiple input variables simultaneously. The goal is to identify the key drivers of uncertainty and to understand the robustness of the model's conclusions.

Sensitivity analysis is crucial for several reasons. It helps in identifying areas where more precise data or refined modeling might be needed. It can also aid in simplifying complex models by highlighting input factors that have negligible effects. Furthermore, it contributes to building confidence in model predictions by demonstrating how sensitive the results are to variations in assumptions and input data. This makes it an indispensable tool for risk assessment, decision-making, and model validation.