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Exam result correlation was strongest for the average ACR score.
As a result, correlation analysis could reveal associations between miRNAs and their target genes as well as non-target genes.
Each statistically supported result (correlation or no correlation between the feature and the outcome) was included and considered as a proven individual observation.
As a result, correlation coefficients indicating more than a moderate association may not be possible when using indicators of physical functioning as validation measures.
The linear regression analysis between chromosome numbers and genome size revealed a positive correlation between these characters, with a relatively high R value of 0.7229 (Fig. 3D); a Pearson correlation analysis confirmed this result (correlation coefficient of 0.85, P < 0.05).
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The resulting correlation values are visualized by generating new edges between correlating nodes.
The resulting correlation coefficient is.
After the linear regression analysis, the resulting correlation coefficient was found to be R2=0.97.
The resulting correlation covers a wide range of porosities, velocities, cell sizes and temperatures.
The resulting correlation matrix shows the influence of the test setup on the study outcome.
Results: Correlation coefficients, reflecting within-subject reproducibility, varied between.68 and.96 (mean,.86).
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