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Comparison analysis between WRF model outputs and observational data were performed to evaluate the model skill in forecasting surface solar irradiance.
Hypothesis tests using measured data were performed to find the severest applied serge condition and to select control factors for the design-of-experiments (DOE).
Multivariate statistical design and principal component analysis (PCA) applied to RP-HPLC-DAD and FTIR spectroscopic data were performed to investigate the fingerprints of four coffee cultivars, traditional red bourbon and three genetically modified cultivars.
A Tukey honest significant difference and Mann–Whitney pairwise tests for non-parametric data were performed to determine a significant of difference in mean canopy height and biomass between each fragmentation category pair.
As above, 10,100 permutations of the data were performed to determine the degree to which obtained estimates were different than those obtained from a random assignment of haplotypes to populations.
For every analysis, 1000 permutations of the data were performed to generate P values; estimates were considered significant if the P value was <0.05 after adjusting for multiple comparisons [55].
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Post-processing of USBL position data was performed to reduce uncertainty associated to the ROV navigation tracks.
Comparisons with experimental data are performed to demonstrate the accuracy of this closure-model.
A thermodynamic analysis of the data was performed to provide fundamental insight into the uptake process.
A comparison with available experimental data was performed to validate the DEM implementation.
Secondly, to define hydraulic habitat feature, a statistical analysis on derived flow data was performed to identify 'habitat suitability'.
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