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CHELPG (CHarges from ELectrostatic Potentials using a Grid-based method) [1] is an atomic charge calculation scheme developed by Breneman and Wiberg, in which atomic charges are fitted to reproduce the molecular electrostatic potential (MESP) at a number of points around the molecule.
Mulliken charges arise from the Mulliken population analysis [1] [2] and provide a means of estimating partial atomic charges from calculations carried out by the methods of computational chemistry, particularly those based on the linear combination of atomic orbitals molecular orbital method, and are routinely used as variables in linear regression (QSAR [3]) procedures. [4]
Selection coefficient, usually denoted by the letter s, is a measure used in population genetics to quantify the relative fitness of a genotype compared to other genotypes. . Selection coefficients are central to the quantitative description of evolution, since fitness differences determine the change in genotype frequencies attributable to selecti
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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 ...
MacLean first introduced the term "limbic system" to refer to this set of interconnected brain structures in a paper in 1952. MacLean's recognition of the limbic system as a major functional system in the brain was widely accepted among neuroscientists, and is generally regarded as his most important contribution to the field.
This is the smallest value for which we care about observing a difference. Now, for (1) to reject H 0 with a probability of at least 1 − β when H a is true (i.e. a power of 1 − β), and (2) reject H 0 with probability α when H 0 is true, the following is necessary: If z α is the upper α percentage point of the standard normal ...
In statistics, the method of moments is a method of estimation of population parameters.The same principle is used to derive higher moments like skewness and kurtosis. It starts by expressing the population moments (i.e., the expected values of powers of the random variable under consideration) as functions of the parameters of interest.