Search results
Results from the WOW.Com Content Network
Phenylhydrazine was the first hydrazine derivative characterized, reported by Hermann Emil Fischer in 1875. [7] [8] He prepared it by reduction of a phenyl diazonium salt using sulfite salts.
The molecular formula C 6 H 8 N 2 may refer to: Adiponitrile; 1,4-Diisocyanobutane; Dimethylpyrazine, an alkylpyrazine; 2-Methylglutaronitrile; 2-Picolylamine; Phenylenediamines. o-phenylenediamine; m-phenylenediamine; p-phenylenediamine; Phenylhydrazine
In statistical thermodynamics, the UNIFAC method (UNIQUAC Functional-group Activity Coefficients) [1] is a semi-empirical system for the prediction of non-electrolyte activity in non-ideal mixtures. UNIFAC uses the functional groups present on the molecules that make up the liquid mixture to calculate activity coefficients .
Adiponitrile is an organic compound with the chemical formula (CH 2) 4 (CN) 2. This viscous , colourless dinitrile is an important precursor to the polymer nylon 66 . In 2005, about one million tonnes of adiponitrile were produced.
The sample mean and sample covariance are not robust statistics, meaning that they are sensitive to outliers. As robustness is often a desired trait, particularly in real-world applications, robust alternatives may prove desirable, notably quantile-based statistics such as the sample median for location, [4] and interquartile range (IQR) for ...
An example of the difference is the empirical formula for glucose, which is CH 2 O (ratio 1:2:1), while its molecular formula is C 6 H 12 O 6 (number of atoms 6:12:6). For water, both formulae are H 2 O. A molecular formula provides more information about a molecule than its empirical formula, but is more difficult to establish.
In statistics, the method of estimating equations is a way of specifying how the parameters of a statistical model should be estimated. This can be thought of as a generalisation of many classical methods—the method of moments , least squares , and maximum likelihood —as well as some recent methods like M-estimators .
In the theory of probability, the Glivenko–Cantelli theorem (sometimes referred to as the Fundamental Theorem of Statistics), named after Valery Ivanovich Glivenko and Francesco Paolo Cantelli, describes the asymptotic behaviour of the empirical distribution function as the number of independent and identically distributed observations grows. [1]