Sentence examples for most significant statistical from inspiring English sources

The most significant statistical properties which are exclusive for each type of fault are proposed here as classification criteria.

It is found that the well known method that maps the Pearson correlations for Y to δij is the least robust, suffering the most significant statistical uncertainty.

The most significant statistical finding showed that the ethnic, gender and rank breakdown of officers sent to disciplinary panels for termination or lengthy suspensions roughly matched the demographics of the LAPD as a whole — a conclusion that department officials emphasized to rebut officers' notions of bias.

The most significant statistical correlations observed in patients with S. aureus infections were between the total number of CD14+ monocytes and CD14+ monocyte subpopulations and several gene expression modules (Figure 8).

ROC curves emphasize the most significant statistical differences between cases and controls.

We checked multiple alternative parameters for each program, and the conditions finally chosen were those which provided the most significant statistical value.

Analyses of risk factors for caries in Brazilian adolescents have pointed out that the following variables: past history of caries [ 21], activity of the disease, parents' educational level [ 22] and socioeconomic factors [ 10, 11] were shown to be the most significant in statistical models.

Most of the significant statistical associations we observe appear plausible; for example, the significantly elevated exposures to chloroform, p-dichlorobenzene, d-limonene, and β-pinene are consistent with existing data on indoor sources, as is the observed relationship between ETS, benzene, and styrene (Wallace 1991a, 1991b).

These factors are well known to be important in determining the accuracy of variant calls and, not surprisingly, were the most significant in the authors' statistical analysis [ 6].

SUV41% was the most time-dependent parameter, with significant statistical differences between R1.5 and R2 versus R5 and R10 and between R2.5 and R10 (p < 0.0001) (Table 2).

To select the GHMs most significant for face recognition, a statistical learning approach is adopted.