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There are two major types of problems in uncertainty quantification: one is the forward propagation of uncertainty (where the various sources of uncertainty are propagated through the model to predict the overall uncertainty in the system response) and the other is the inverse assessment of model uncertainty and parameter uncertainty (where the ...
Typical volumes are 1, 2, 5, 10, 20, 25, 50 and 100 mL. Volumetric pipettes are commonly used in analytical chemistry to make laboratory solutions from a base stock as well as to prepare solutions for titration. ASTM standard E969 defines the standard tolerance for volumetric transfer pipettes. The tolerance depends on the size: a 0.5-mL ...
For example, 13 0 0 has three significant figures (and hence indicates that the number is precise to the nearest ten). Less often, using a closely related convention, the last significant figure of a number may be underlined; for example, "1 3 00" has two significant figures. A decimal point may be placed after the number; for example "1300."
4. The solution is to expand the function z in a second-order Taylor series; the expansion is done around the mean values of the several variables x. (Usually the expansion is done to first order; the second-order terms are needed to find the bias in the mean. Those second-order terms are usually dropped when finding the variance; see below). 5.
Interactions in the Standard Model. All Feynman diagrams in the model are built from combinations of these vertices. q is any quark, g is a gluon, X is any charged particle, γ is a photon, f is any fermion, m is any particle with mass (with the possible exception of the neutrinos), m B is any boson with mass. In diagrams with multiple particle ...
A p-box (probability box). A probability box (or p-box) is a characterization of uncertain numbers consisting of both aleatoric and epistemic uncertainties that is often used in risk analysis or quantitative uncertainty modeling where numerical calculations must be performed.
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The methodology deals with models whose results are expressed as probability distributions of possible outcomes, often in the form of Monte Carlo simulations, and the problem can be viewed as assessing, and comparing between models, how good these representations of uncertainty are.