Sentence examples for explaining variability from inspiring English sources
Slope, relative elevation and the potential solar radiation index were the variables that contributed the most to explaining variability in NDVI for raw data.
Population approaches to define pharmacokinetics and pharmacokinetic/pharmacodynamics are now more currently used to define dosing regimens, adapted to the different paediatric and neonatal age groups, that allow to increase efficacy and reduce toxicity, by taking into account factors explaining variability in drug response.
Both specifications are satisfactory in terms of explaining variability in the data measured through the pseudoR2 sTheispecificationpecification with both SSW and SSA is the preferred one.
Using a finite element model, we demonstrate that the balance between scar stiffening due to collagen accumulation and increased wall stresses due to infarct thinning can produce either expansion or compaction in the pressurized heart-potentially explaining variability in the literature-and that loaded dimensions are much more sensitive to changes in thickness than in stiffness.
Therefore, a larger relative contribution of non-specific inflammation is expected in wild populations than we have found in captive birds for explaining variability in local skin swellings.
Under this hypothesis, we predicted that if urban invaders belong to the group of tame species then the main factor explaining variability in invasiveness among species should be their mean FID (MFID) measured in rural (i.e. 'natural') habitats.
None of the other variables explained variability in MIDAS score.
Also shown are the first five variables (explained variability in %) that could best explain the variability in ANC, TP, and TOC, using RDA and stepwise forward selection with the order of selection shown in parentheses.
They then examined whether these psychological variables helped explain variability in health risk within this community.
PLS finds latent variables (LVs) that explain variability observed in the dependent measures (AEPs), which directly covary with experimental conditions (e.g., groups, sessions).
Since these LUR variables had been used to explain variability in outdoor NO2 in these cities we therefore expected that they would explain variability in dust hopanes concentrations.
