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Quality dose rate distribution datasets of the HDR sources used in a clinical treatment are required.
Two root distribution datasets of 'Veronese' poplar (Populus deltoides x nigra) were used to calibrate a root distribution model for application on single root systems and to interacting root systems at the hillslope scale.
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Categorical data were summarised as number (percentage) of subjects/lesions; continuous data were summarised as mean, standard deviation, median and range The normal distribution of datasets of different variables was assessed by means of the D'Agostino-Pearson test.
A georeferenced distribution dataset was constructed of all households in the 2 study districts using Google Earth satellite imagery.
The normality of the distribution of datasets was checked with Kolmogorov-Smirnov test.
We compared the distance class distribution of simulated datasets of 1000 "artificial hybrids" (generated as above) with that observed in D. galeata populations dominated by a single clone.
Note that the weights here aim to leverage any possible asymmetric distribution within the datasets of the above subterms MI i and Cor i.
Figure 3a shows the distribution of datasets as the ratio within each study of the number of probes with higher CV in males, divided by the number of probes with CV higher in females.
Vanted offers a series of tests for calculation of statistical parameters, for testing the normal distribution of datasets (David Quicktest [ 47]) and for outlier detection (Grubbs test).
We also compared distance distributions for the datasets of less and more than 125 sequences (see Methods) with the distance distribution of randomly selected non-coevolved site pairs.
Owing to non-normal distribution of datasets (P<0.001, Kolmogorov Smirnov test), nonparametric statistics were used in our study.
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