What a doozy, right?
First, let me say, I am by no means a chemometrician. I'm a Chemist by schooling and trade, but I'm having some difficulty coming up with a "real-world" explaination for what Q Residuals and T^2 actually "tell you" about a sample set.
I've collected 5 spectra of 3 different liquers (Cointreau, Southern Comfort and Knob Creek) and put them through the Eigenvector Solo ringer. After minimal pre-processing (only doing Mean Centering), if I plot Q Residuals (y-axis) versus T^2 (x-axis) I get the below:
What "real-world" statement can I say about the liquors, based on the plot? Is it correct to say that there is little separation within the model (the T^2 is practically the same for all 3)? Can I say that because there is separation across Q (the y-axis), I can tell the 3 liquors apart from one another?
At the end of the day, what is T^2 and Q actually telling me about this particular group of samples? Thanks for any help!
For the discussion of math. Duh.
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