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R square, the square of Pearson's correlation is a measure of how much variability in one variable is explained by the variability in the other.
Specifically the correlation values were found to be confined in a narrow [-0.1 0.1] interval around zero for different types of variability profiles; i.e. less than 10% of the variance in signal conservation variable can be explained by the variability values.
The CCA study demonstrated that more that 60% of the evolution of inner bars can be explained by the variability of outer bars.
The distribution of QF and QI forests was significantly explained by the variability in soil available water-holding capacity and rock fragment content, QF forests appearing on soils with over 22 mm of available water-holding capacity and < 26% rock fragments.
Differences in the root distribution within the same field site may be explained by the variability of the initial planting material and local variation of environmental factors.
Differences between the results from previous studies or their interpretation could be explained by the variability of the adopted research designs, procedures (e.g. the periods of data collection, utilisation of recording devices) or data analysis methods.
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Despite known individual risk-factors were accounted for in the single-level model, the high variability explained by the variable "clinical-centre" states its importance in predicting 30-day mortality after CABG.
The time trends function described the mortality changes catching decadal to decadal fluctuations, and leaving year-to-year variability to be explained by the climate variability variables.
Using canonical correlation analysis (CCA) we also test whether element variability in the claw keratin of a terrestrial carnivore could be explained by the chemical variability in the soils of the local environment.
Spatial patterns in the organization of convective initiation are proposed to be explained by the spatial variability of vegetation and soil moisture patterns on altitudinal gradients, and by how this translates into the spatial variability of the diurnal cycle of latent heating fluxes between the land surface and the lower troposphere.
Such uneven pattern could be explained by the spatial variability of nutrients content in soil, for example, the nitrogen was abundant in some area but deficient in other parts of the field.
More suggestions(12)
explained by the diversity
explained by the volatility
explained by the dispersal
indicated by the variability
described by the variability
explained by the discrepancy
explained by the variance
explained by the disparity
explained by the variety
explained by the variations
explained by the changes
explained by the variable
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