What is the role of orthogonality in PCA components?

Orthogonality ensures components are uncorrelated and capture independent variance directions.

PCA enforces orthogonality between principal components, meaning each component captures unique variance not explained by others. This eliminates redundancy and simplifies interpretation of variance structure. Orthogonality arises from eigen decomposition of symmetric covariance matrices.