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The amount of variance explained by each principal component is shown in brackets.
Component scores indicate the amount of variance explained by each PC.
The second level partitioned the amount of variance explained by plot, patch, and landscape factors alone and in combination.
The total amount of variance explained by all the independent variables in the regression models was computed.
Thus, the amount of variance explained by person variables was only about half as much for numeracy compared to literacy.
The amount of variance explained by a given predictor variable is the square of the correlation between that variable and the behavior in question.
The amount of variance explained increased only ~ 2 percentage points (pp), less than that obtained by including the kriging step, which explained 4 pp.
Such asynchrony also increases intra-annual variability, reducing the amount of variance explained by time in the regression analyses.
As in both analyses several group number models were similar in the amount of variance explained, we also present the group configurations for these alternative outcomes (Table 3).
This method estimates the amount of variance explained by every possible frequency in the time series (and is the unsmoothed variant of spectral analysis).
In those cases data are simulated based upon the amount of variance explained by the genetic model, which is then further partitioned into main effect and interaction terms.
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