1) this doesn't work for cases where your data are positive-definite.
However, let's set that aside. I apologize for being a bit obfuscatory. My point is: If this is the case, then the explanation in the OP is totally misleading, because your data shouldn't look like an ellipsoid, but rather a circle. PCA should only be used in situations where there is a reason to believe there is a mechanistically justifiable "hidden value" that underlies otherwise uncontrolled "independent variables", thus making a dimensional reduction reasonable.
This is not at all the situation that the OP goes over in the first part of the post.
However, let's set that aside. I apologize for being a bit obfuscatory. My point is: If this is the case, then the explanation in the OP is totally misleading, because your data shouldn't look like an ellipsoid, but rather a circle. PCA should only be used in situations where there is a reason to believe there is a mechanistically justifiable "hidden value" that underlies otherwise uncontrolled "independent variables", thus making a dimensional reduction reasonable.
This is not at all the situation that the OP goes over in the first part of the post.