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Advisor(s)
Abstract(s)
Beyond the classical statistical approaches (determination of basic statistics, regression
analysis, ANOVA, etc.) a new set of applications of different statistical techniques has
increasingly gained relevance in the analysis, processing and interpretation of data
concerning the characteristics of forest soils. This is possible to be seen in some of the
recent publications in the context of Multivariate Statistics. These new methods require
additional care that is not always included or refered in some approaches. In the particular
case of geostatistical data applications it is necessary, besides to geo-reference all the data
acquisition, to collect the samples in regular grids and in sufficient quantity so that the
variograms can reflect the spatial distribution of soil properties in a representative
manner. In the case of the great majority of Multivariate Statistics techniques (Principal
Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact
they do not require in most cases the assumption of normal distribution, they however
need a proper and rigorous strategy for its utilization. In this work, some reflections about
these methodologies and, in particular, about the main constraints that often occur during
the information collecting process and about the various linking possibilities of these
different techniques will be presented. At the end, illustrations of some particular cases of
the applications of these statistical methods will also be presented.
Description
Keywords
Data acquisition Statistical data analysis Multivariate statistics Forest soils