Sentence examples for significance limits for from inspiring English sources

Significance limits for these averaged spectra were computed as described in Evans and Baker (2003); this method adjusts the limits on the individual spectra to reflect the improved confidence achieved in averaging multiple independent measures.

The assumptions we have made on the clinical and statistical significance limits for a diagnostic association, and the method we have used to interpret and summarise such diagnostic associations in different populations, are presented to the scientific community for discussion.

All the statistical analyzes were performed using SPSS v. 18 (IBM, Chicago, IL, USA), and a two-tailed P<0.05 was considered as the significance limit for each of the different tests.

To this end, the correlation maps are thresholded at the significance limit for a corresponding univariate test (e.g., | r| ≥ 0.288 for a sample size of 47 at α = 0.05. Note that this thresholding rule only constitutes a convention; one could as well use larger or smaller threshold values resulting in more or less localized clusters).

Examining Table 5, we can conclude that the null hypothesis is accepted with p-values above the traditional statistical significance limit of 0.05 for the majority of bug types except for "Deadlock-Data race", "Deadlock-Order violation" and "Deadlock-Suspension" pairs where the null hypothesis is rejected.

We use a traditional statistical significance limit of 0.05 and Vargha and Delaney's suggestion [28] for statistical significance.

A significance limit of P<0.05 was set.

Statistical analysis was performed using GraphPad Prism (GraphPad Software Inc., La Jolla, CA, USA) and data were compared using a Kruskal-Wallis test with Dunn post-test with significance limit set for P < 0.05.

Significance limits were set at P < 0.05.

Although the use of P<0.05 as significance limit is appropriate for a replication study verifying reported associations, the occurrence of false negative findings cannot be excluded.

A metabolite was considered significant if it had a univariate p-value≤0.05 and was important for class separation in the OPLS-DA model, according to the variable weight or covariance loading (w*) (here the significance limit was w* >|0.03| for the models separating non-infected controls and enteric fever samples and w* >|0.07| for models between S. Typhi and S. Paratyphi A).