November 30, 2024
Linearity of Correlations and Maximum Agreement
A person's self identity is defined by who they think they are, how other people tell who they are, and how in general one can be understood as a human. The previous two is nice to be linearly correlated, because that would make it easier for people to collaborate toward the same direction. If not linear, the other illustrations can be a feedback loop, which depends on who the other person is, or a hall of mirrors, which is about a self perception. The third one can be the most useful, when one can be addressed as human, then things would be common, or not uncommon.
Linear regressions are the most common type of correlations, because there is no up and down, or the indication is that the up and down can be ignored. This is the vital step to build up a network when any two of the items is seen as either coexistance or linearly correlated.