Uncertainty propagation refers to the process of determining how uncertainties in input variables affect the uncertainty in the output of a model or system. It is crucial for understanding the reliability of predictions made by mathematical models, especially when those models involve complex calculations or multiple uncertain parameters. By analyzing how errors and uncertainties propagate through a model, one can identify which variables have the most significant impact on the outcomes and thus prioritize efforts for improving measurement and accuracy.
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