Sentence examples for an extreme data from inspiring English sources

However, OD values for this particular position contained an extreme data point measured in one of the three exposure runs (i.e. the normalized OD was >140%).

With regard to CS distribution, no significant differences according to adjusted p-values (ANOM) could be detected in the cultivation base module (except for a single position in the WST-1 analysis, which was produced by an extreme data point in one of the three runs).

For such an extreme data set, it is unlikely that any reasonable objective function would assign an optimal score to the biologically correct alignment.

Nevertheless, in this kind of projects, it is not possible to leave out an analysis of extreme data given that this could entail an important risk of working with data which, almost certainly, do not belong to the target population.

Regardless of the approach, regulators must also define a standard for how extreme data must be before the null hypothesis is rejected.

Onavo found that the difference between Twitter for iPhone and TweetDeck could be as much as $2 a session, under the most extreme data plans.

The use of monitored extreme data allows (a) the reduction of uncertainties associated with numerical models, and (b) the validation and updating of existing prediction models and, sometimes, the creation of novel models.

Using this correction in our case examples shows that including or excluding zero total event trials can change the clinical implication of a meta-analysis pooling similarly extreme data, regardless of the effect measure used.

The use of robust regression methods allows reduction of the contribution of extreme data points in a data set.

A conservative, but reasonable, option would be to look for influential data only among the very extreme data in such a way that will not prejudice areas of distribution that are closest to the centre.

The investigation of outliers is required since "deterministic frontier models have the drawbacks of not allowing random noise in the data generating process and, as a result, being very sensitive to extreme data points and outliers" [ 24].