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The present study assesses the spatial distribution of 133 socioeconomic indicators compared with indexes of land vulnerability to natural/human-induced soil compaction in 8101 municipalities in Italy using an exploratory data analysis.
Using an exploratory data analysis tool for lineages through time plots, tree deviation, I identified trees with a significant γ statistic that do not appear to have the characteristic early accumulation of lineages consistent with an early, rapid rate of cladogenesis.
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I use an exploratory data analysis tool, tree deviation, to identify simulated trees that have, throughout their history, had a greater number of taxa than expected under a pure-birth model of diversification.
Using an exploratory descriptive design, data from 164 sophomore nursing students were examined.
Cluster analysis was used as an exploratory data analysis technique to reveal natural grouping from latent patterns in a large data set on the basis of a minimal within-group and a maximal between-group variation, without prejudgment.
Data were interpreted using an exploratory approach for common themes.
In addition, evaluated genes were chosen by a data-driven approach, using the Affymetrix® data as an exploratory data set.
All statistical comparisons were performed two-sided in the sense of an exploratory data analysis using 0.05, 0.01, and 0.001 level of significance.
All statistical comparisons were two-sided in the sense of an exploratory data analysis using P < 0.05 as the level of significance.
For investigation of the obtained data, an exploratory data analysis was performed using SPSS 16 (SPSS Inc., USA) and Excel 2007 (Microsoft Corporation, USA).
In addition, in Section 6 we illustrate the use of our approach by presenting an exploratory data analysis that leverages the information contained by the aforementioned representations, based on the data collected by the visual tool.
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