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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 ...
In computer programming, unspecified behavior is behavior that may vary on different implementations of a programming language. [clarification needed] A program can be said to contain unspecified behavior when its source code may produce an executable that exhibits different behavior when compiled on a different compiler, or on the same compiler with different settings, or indeed in different ...
Uncertainty quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known.
Modifying an object between two sequence points more than once produces undefined behavior. [15] There are considerable changes in what causes undefined behavior in relation to sequence points as of C++11. [16] Modern compilers can emit warnings when they encounter multiple unsequenced modifications to the same object.
In models involving many input variables, sensitivity analysis is an essential ingredient of model building and quality assurance and can be useful to determine the impact of a uncertain variable for a range of purposes, [4] including: Testing the robustness of the results of a model or system in the presence of uncertainty.
In metrology, measurement uncertainty is the expression of the statistical dispersion of the values attributed to a quantity measured on an interval or ratio scale.. All measurements are subject to uncertainty and a measurement result is complete only when it is accompanied by a statement of the associated uncertainty, such as the standard deviation.
The distinction between ambiguity aversion and risk aversion is important but subtle. Risk aversion comes from a situation where a probability can be assigned to each possible outcome of a situation and it is defined by the preference between a risky alternative and its expected value. Ambiguity aversion applies to a situation when the ...
The Ellsberg paradox is based on the difference between these two types of imperfect knowledge, and the problems it poses for utility theory – one is faced with an urn that contains 30 red balls and 60 balls that are either all yellow or all black, and one then draws a ball from the urn.