Looking at the components of a correlation matrix can be an important diagnostic tool. Simply looking at a table of numbers isn’t practical for a matrix larger than say, 4×4, so graphical visualization tools come into play. Various methods have been proposed in the past, from heat maps to correlation ellipses. Taiyun Wei offers an alternative: correlation circles. Positive correlations are illustrated with a filled black circle; negative ones with a white circle outlined in black:
I think this could be a promising approach when there’s a natural ordering amongst the variables in the matrix, as it does pick up patterns in the correlations well, highlighting the distinction between positive and negative correlations. On the other hand, I think it downplays the negative correlations too much — perhaps a filled gray circle rather than the white outlined circle would alleviate that problem.
Now, I think a game of Othello is in order…
Taiyun Wei: Visualization of Correlation Matrix (via Romain François)
