Hello,

I have a list of eigenvectors from Eigenstrat PCA output:

60.922    20.946     8.721     7.292     4.306     2.821     2.765     2.752     2.741     2.725

a 10-dimensional PCA

These eigenvectors sum to > 100, thus the eigenvectors clearly don't signify significance. I remember seeing a PCA plot, where the axes labeled how much each principal component explained the variance.

How can I get these eigenvectors to explain significance of each PCA?