Sentence examples for any variance from inspiring English sources

"We're looking for assistance from City Council and any variance restrictions that can be imposed to keep the neighborhood composition the way it is," Mr. Glover said.

So faithful is the production to the spirit and letter of Waugh's 1945 original that it seems as if its creators feared that any variance or economy might constitute an assault on the entire enterprise of literature itself.

The input into the neural networks was normalized to remove any variance.

The other thing Kobo has done a great job of here is managing to produce an even, highly legible reading light that covers the whole screen and doesn't appear to offer any variance in intensity.

Discriminant validity exists if the items share more common variance with their respective construct than any variance that construct shares with other constructs.

This model was tested with data from all years to determine the overall fit of the model to the data as well as any variance in that fit.

Any variance that stems from time-invariant differences among the units of analysis can be absorbed, i.e., controlled for, by the usage of firm fixed effects.

Murata does not show any variance in its result, that is, no error bars in result figures because its estimation is a deterministic algorithm, while the first two plots show variance due to the stochastic nature of particle filters.

In addition, it is unclear whether benchmarks were run across the range of available servers to account for any variance in performance of the underlying hardware, and here storage speeds themselves would be of interest not least to be able to factor these out.

Presumably, all words should be known to the target group(s) of learners so that any variance in performance on the test would represent learners' individual differences in network knowledge rather than how many words (in the test) they actually know, which would be the focus of a vocabulary size test.

Especially any variance-to-mean dependence remaining after the log2 variance stabilizing transformation will affect the regularized t-statistic when this is based on the assumption of homoscedasticity (i.e. homogeneity of variance), which is the case for limma and SAM.