PCA on correlation and covariance matrixHello,
I am not an expert user so please be gentle with me.
I have performed PCA on some standardised data (with 2 variables) in JMP14 and noted that the two scores plots are almost mirrored across the PC1 axis. Why are they reflected in this manner? (Also, they are not perfect reflections. Why is this?)
AnalyticsWindowsRe: PCA on correlation and covariance matrixSorry, I should have pointed out that the "mirror images" refer to PCA performed on the correlation matrix and the covariance matrix.
Re: PCA on correlation and covariance matrixThe covariance is the fundamental quantity, but the analysis is dominated by the measures with the largest scales and ranges. Centering and scaling first can help avoid the dominance of a few variables. You standardized the data first, so the covariance and correlation results well be similar.
