Explain the concept of "sensitivity analysis."

Sensitivity analysis is a method used to assess how the variability in the output of a model can be attributed to different variations in its inputs. In this context, it involves evaluating how changes in the values of an independent variable affect a specific dependent variable. This is particularly useful in decision-making processes and risk assessment, as it allows analysts to understand the degree to which uncertainties in input variables can influence the results.

By altering the values of independent variables systematically, analysts can observe the effects on the dependent variable, which can help identify which inputs have the most significant impact on outcomes. This knowledge can inform strategic choices and improve resource allocation. Sensitivity analysis is widely applied in various fields, including finance, engineering, and environmental modeling, for its capacity to highlight influential factors and guide operational strategies effectively.

The other options do not capture the essence of sensitivity analysis as accurately. For instance, determining fixed values does not involve the variability that sensitivity encompasses. Similarly, measuring the impact of consistent data and analyzing historical trends do not convey the interactive nature of independent and dependent variables, which is central to understanding sensitivity analysis.