The phrase "average squared deviations" is correct and usable in written English.
It can be used in statistical contexts, particularly when discussing measures of variability or dispersion in a dataset.
Example: "To calculate the variance, we first need to find the average squared deviations from the mean."
Alternatives: "mean squared deviations" or "mean of squared differences".
We sampled one hundred mutations per mutable entity, wi, of the network and averaged their effect, to obtain μ ¯ i, p (average squared deviation from the non-mutated network output) on each of the P = 100 network outputs or fitness-linked phenotype.
E x) = Σxf(x) (2) E x) = ∫xf(x dx (3) The variance of a random variable, denoted by Var(x) or σ2, is a weighted average of the squared deviations from the mean.
The characteristic value was chosen as follows: all expression values for a gene were randomly divided onto two groups, and average and sum of squared deviations were calculated for each group.
Instead, we turned to Approximate Bayesian Computation, using as our summary statistic the sum of the squared deviations of the average simulated RNA concentrations (and average fraction of virions for MOI 10) from their corresponding empirical means.
These measures are either based on the RMSD (root mean squared deviation: average squared distance between homologous alpha carbons) or the dRMSD (distance RMSD: average square difference of distances between equivalent pairs of amino acids) like the DALI score (Holm and Sander, 1995), APDB (O'Sullivan et al., 2003) or the iRMSD (Armougom et al., 2006a).
The stochastic approach coupled to high dimension of data and large numbers of parameters led the authors to choose an approximate Bayesian computation using as summary statistic the sum of the squared deviations of the average simulated RNA concentration.
In particular, he defined an inter-ensemble RMSD (eRMSD), whose square value is the average mean square deviation between conformations in two ensembles.
SSD: sum of squared deviations.
Applying rigid transformation protocols, population of the detected domain building models with an average root mean square deviation from native structures of 2.3 Å and an average template modeling score from native structures of 0.43 has been obtained.
