Uncertainty analysis is a field of study that deals with the quantification and characterization of various sources of uncertainty in scientific and engineering models. This analysis involves identifying and evaluating the impact of uncertainties in input parameters, model assumptions, and data on the output results of a model or simulation. The goal of uncertainty analysis is to provide insights into the reliability and robustness of model predictions, as well as to help decision-makers assess the risks associated with different scenarios and outcomes. Various statistical methods, sensitivity analysis techniques, and probabilistic modeling approaches are used in uncertainty analysis to assess, propagate, and quantify uncertainties in a systematic and comprehensive manner. Ultimately, uncertainty analysis helps improve the quality and credibility of model-based predictions and recommendations by informing stakeholders about the level of confidence and accuracy in the results.