Sentence examples for most important correlation from inspiring English sources

To analyze their applicability and the amount of conservatism, the most important correlation formulas have been compared with measured JR-curves for different German reactor pressure vessel steels.

Briefly, this plugin gives access to the most important correlation coefficient-based tools (Pearson's coefficient, Manders' coefficient) and allows comparing various methods (Costes' approach, Van Steensel's approach, Li's approach) to evaluate the co-localisation [49].

The most important correlation involving variables of study 2 was of.583 (CI:.521 and.639), between object and viewpoint agreement, and was followed by a correlation of.382 (CI:.303 and.456) between object agreement and familiarity.

Several children had several diagnoses, and the most important correlation was observed between eczema and food allergy (p < 0.001).

The dual practitioners had higher levels of debt and thus more negative net capital income than their non-dual practicing colleagues did, and this was the most important correlation after gender and children.

Consequently, the first few SVD components contain the most important correlations while the last few components contain the least correlated information and are typically considered to be noise.

The model for traffic flow simulation includes a statistical treatment of most significant variables involved, and some original techniques to account for the most important correlations found in actual traffic.

This implies that correlations beyond the preceding sign are important, though the most important correlations comes from the preceding sign.

The most important correlations involve the chromosomal loci 6p22, 16q, 1p31, and 5q33, and these associations will be analyzed in detail.

The most important correlations are displayed as scatterplots with the fitted regression lines for the following parameters: DVR convolution versus DVR deconvolution), Yret versus fret), and DVR convolution versus Yret), DVR deconvolution versus fret).

Most important, correlations of AOD and PM2.5 may reflect variability in PM2.5 that could be predicted by other sources of information, such as land use or meteorology or estimation of large-scale regional variation through spatial smoothing of monitored values, so they may overstate the usefulness of AOD as a predictor in light of other readily available information.