Intercorrelation between parameters or constituents

That is an important part of the previous knowledge we should have before to run a model or calibration. In this case I use the LUCAS database with the Spanish samples and run the correlation matrix for the constituents:

In this case we get a number , but we can see the XY plot as well for a better understanding of the correlation between the parameters:

The strongest correlation is the one between Organic Carbon and Nitrogen, but the other ones are interesting to observe as well.

To know  in advance these correlations help us to interpret better the regression coefficients once the models are developed, the same as the correlation spectrum for every parameter which shows at which wavelengths are the highest correlations with the parameter of interest (in this case with Clay)