The phrase "a final correlation" is correct and usable in written English.
It can be used when discussing the last or concluding relationship or connection between two or more variables or data points in a study or analysis.
Example: "After analyzing the data, we found a final correlation between the two variables that confirmed our hypothesis."
Alternatives: "a concluding relationship" or "a definitive link".
A final correlation was carried out between numerical predictions and experimental results of the damaged regions in the component at several load levels.
A final correlation matrix is created based on either the Spearman's, Pearson's or normal score correlation between each pair of binned datasets.
Lastly, to threshold, a final correlation between the systemic O2sat and the time-courses of individual voxels of was computed (Pearson's linear correlation).
Multiple correlations for a pair of genes from different datasets were then combined to produce a final correlation value for a specific gene pair.
The canonical way to compute the correlation between a label and the microarray data is to compute the correlation between the label (first variable) and every single gene (second variable), and to combine the results in a final correlation coefficient.
If there are n datasets, and each reports a correlation of xi for a gene pair, the final correlation value is computed by corr = Σ i(x i * s i /Σ i(s i) where i ∈ [1, 2,..., n], and si represents the number of samples in data set i. Every interaction in DroID is annotated with the current gene expression correlation value for that pair.
This led them to conduct a final direct correlation of the face inversion effect: they computed the difference in recognition performance for upright and inverted faces and did the same for the corresponding fMRI responses, and then correlated the two derived measures.
The third bootstrap sample was used to compute the final correlation of the chosen subset and used as a performance measure.
And this may explain one final correlation.
Empirical polynomial models were employed to analyze the effects of the process variables on the response factors and the final correlation coefficients obtained were above 95%.
The final correlation was able to predict the longitudinal pressure gradient of the flow of agricultural residues (i.e., non-wood fibres) as biomass slurries in pipes and, with a small uncertainty (<10%), could be applied to design commercial pipelines to hydraulically transport various agricultural residue biomass slurries.
