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The "bandwidth" in which a value may be observed.
There are many uncertainties associated with the estimation of risk. An understanding of uncertainties associated with data, methods and models used to identify and estimate the risks involved plays an important part in their application. Uncertainty analysis involves the determination of the variation or imprecision in the model results, resulting from the collective variation in the parameters and assumptions used to define the model. An area closely related to uncertainty analysis is sensitivity analysis. Sensitivity analysis involves the determination of the change in response of a model to changes in individual model parameters.
Estimating uncertainty consists of translating uncertainty in the crucial model parameters into uncertainty in the outputs of the risk model. The completeness and accuracy of the risk estimation should be stated as fully as possible. Sources of uncertainty should be identified where possible. This should address both data and model uncertainties. Parameters to which the analysis is sensitive should be stated.