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Estimation (or estimating) is the process of finding an estimate or approximation, which is a value that is usable for some purpose even if input data may be incomplete, uncertain, or unstable. The value is nonetheless usable because it is derived from the best information available. [ 1 ]
In statistics, a circumflex (ˆ), called a "hat", is used to denote an estimator or an estimated value. [1] For example, in the context of errors and residuals , the "hat" over the letter ε ^ {\displaystyle {\hat {\varepsilon }}} indicates an observable estimate (the residuals) of an unobservable quantity called ε {\displaystyle \varepsilon ...
The simplest form of a group-contribution method is the determination of a component property by summing up the group contributions : [] = +.This simple form assumes that the property (normal boiling point in the example) is strictly linearly dependent on the number of groups, and additionally no interaction between groups and molecules are assumed.
Partition coefficients can be measured experimentally in various ways (by shake-flask, HPLC, etc.) or estimated by calculation based on a variety of methods (fragment-based, atom-based, etc.). If a substance is present as several chemical species in the partition system due to association or dissociation, each species is assigned its own K ow ...
The residual is the difference between the observed value and the estimated value of the quantity of interest (for example, a sample mean). The distinction is most important in regression analysis, where the concepts are sometimes called the regression errors and regression residuals and where they lead to the concept of studentized residuals.
The Avogadro constant, commonly denoted N A [1] or L, [2] is an SI defining constant with an exact value of 6.022 140 76 × 10 23 mol −1 (reciprocal moles). [3] [4] It is this defined number of constituent particles (usually molecules, atoms, ions, or ion pairs—in general, entities) per mole and used as a normalization factor in relating the amount of substance, n(X), in a sample of a ...
In general, with a normally-distributed sample mean, Ẋ, and with a known value for the standard deviation, σ, a 100(1-α)% confidence interval for the true μ is formed by taking Ẋ ± e, with e = z 1-α/2 (σ/n 1/2), where z 1-α/2 is the 100(1-α/2)% cumulative value of the standard normal curve, and n is the number of data values in that ...
The strength of a bond can be estimated by comparing the atomic radii of the atoms that form the bond to the length of bond itself. For example, the atomic radius of boron is estimated at 85 pm, [10] while the length of the B–B bond in B 2 Cl 4 is 175 pm. [11] Dividing the length of this bond by the sum of each boron atom's radius gives a ratio of