Typically, PCA is used to reduce the dimensionality of a data set, while retaining as much of the original information as possible. This reduction is achieved by transforming the original set of variables into a new smaller set of variables, the principal components, which are uncorrelated and the first few principal components (PCs) retain most of the variation present in the original variables.
XRD study of soil samples has been done to find the phases in the sample. First, silica is removed from the sample following a slightly modified procedure ofwho used the method to avoid the matrix effect caused by silica in determination of selenium in soil samples by graphite-furnace atomic- absorption spectrometry.