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Added plotted variables at the axes, and added μ values.
For graphical representations, the variable (pathways) plot and the individual (genomes) plot were combined, restricting plotted variables to those with a quality of representation greater than 0.75, in order to conserve interpretability.
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A comparison of the two stages was made by plotting variables on the same graph.
The data set was checked for logical inconsistencies, illegal codes, omissions and improbabilities by tabulating, summarising, describing and plotting variables.
Residuals based on the initial model were plotted against variables from the different sets of physical variables to determine which among these was predictive of daily endotoxin concentration.
The research analysed 58 variants of the tales and looked at 72 plot variables.
Other plot variables included: temperature, precipitation, incident solar loading, and canopy openness.
The model predicted the interaction of subplot and whole plot variables as well as their importance.
Bird abundance and richness were influenced by plot variables (increased with stand age) and landscape variables (decreased with the amount of shrublands and eucalyptus stands surrounding the plot).
At each plot, variables were calculated and derived from DAYMET data, digital elevation models, and soil surveys and assessed for precision and ability to model forest type distributions.
We then tested relationships between (i) trade-off plot variables and (ii) independent variables related to keypress intensity, which might share features with established theories of valuation.
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