Usually applied to future events, costs and benefits, even though interpretation of the past is notoriously subject to many uncertainties. Sometimes attempts to 'quantify' uncertainty are made by assigning probabilities based on past experience or derived by judgments of various kinds. Sometimes alternative scenarios of the future are devised. Out of the infinity of possible futures, the art lies in trying to narrow down the range to a manageable set of imaginable possibilities that, between them, encompass what are seen as the main characteristics of these possibilities. The reduction of uncertainty about the financial consequences of ill-health (health care expenditures and loss of earnings due to sickness) is the principal advantage of and rationale for health insurance.
Analysts distinguish between stochastic uncertainty (sometimes 'first-order uncertainty') and subjective uncertainty (sometimes 'second-order uncertainty'). The former is uncertainty arising from randomness in the data studied. The second is uncertainty relating to parameter values and is due to insufficient knowledge. See Bayesian Method, Cost-effectiveness Plane, Expected Utility Theory, Frequentist Approach, Insurance, Prospect Theory, Regret Theory, Sensitivity Analysis.
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