I've conducted principal component analysis (PCA) with
FactoMineR R package on my data set. I have a general question:
Given that the first and the second dimensions of PCA are orthogonal, is it possible to say that these are opposite patterns?
For example, can I interpret the results as: "the behavior that is characterized in the first dimension is the opposite behavior to the one that is characterized in the second dimension"? I know there are several questions about orthogonal components, but none of them answers this question explicitly.