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Concept
Uncertainty
Summary
Uncertainty refers to epistemic situations involving imperfect or unknown information. It applies to predictions of future events, to physical measurements that are already made, or to the unknown. Uncertainty arises in partially observable or stochastic environments, as well as due to ignorance, indolence, or both. It arises in any number of fields, including insurance, philosophy, physics, statistics, economics, finance, medicine, psychology, sociology, engineering, metrology, meteorology, ecology and information science.
Although the terms are used in various ways among the general public, many specialists in decision theory, statistics and other quantitative fields have defined uncertainty, risk, and their measurement as:
The lack of certainty, a state of limited knowledge where it is impossible to exactly describe the existing state, a future outcome, or more than one possible outcome.
Measurement of uncertainty A set of possible states or outcomes where probabilities are assigned to each possible state or outcome – this also includes the application of a probability density function to continuous variables.
In statistics and economics, second-order uncertainty is represented in probability density functions over (first-order) probabilities.
Opinions in subjective logic carry this type of uncertainty.
Risk is a state of uncertainty, where some possible outcomes have an undesired effect or significant loss. Measurement of risk includes a set of measured uncertainties, where some possible outcomes are losses, and the magnitudes of those losses. This also includes loss functions over continuous variables.
There is a difference between uncertainty and variability. Uncertainty is quantified by a probability distribution which depends upon knowledge about the likelihood of what the single, true value of the uncertain quantity is. Variability is quantified by a distribution of frequencies of multiple instances of the quantity, derived from observed data.
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