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Uncertainty may be implied by the last significant figure if it is not explicitly expressed. [1] The implied uncertainty is ± the half of the minimum scale at the last significant figure position. For example, if the mass of an object is reported as 3.78 kg without mentioning uncertainty, then ± 0.005 kg measurement uncertainty may be implied.
Significant figures is a rough approximation to uncertainty, and commonly rounded to integers. One decimal digit is worth 3.32 bits. Note that the actual precision can vary, such that 100 has two significant digits and 999 has 2.9996 digits.
Uncertainty or incertitude refers to 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. [1]
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.
A volumetric pipette, bulb pipette, or belly pipette [1] allows extremely accurate measurement (to four significant figures) of the volume of a solution. [2] It is calibrated to deliver accurately a fixed volume of liquid.
Confidence bands can be constructed around estimates of the empirical distribution function.Simple theory allows the construction of point-wise confidence intervals, but it is also possible to construct a simultaneous confidence band for the cumulative distribution function as a whole by inverting the Kolmogorov-Smirnov test, or by using non-parametric likelihood methods.
The uncertainty theory invented by Baoding Liu [1] is a branch of mathematics based on normality, monotonicity, self-duality, countable subadditivity, and product measure axioms. [ clarification needed ]
In statistics, propagation of uncertainty (or propagation of error) is the effect of variables' uncertainties (or errors, more specifically random errors) ...