*Eigenvectors* are used for understanding linear transformations. In data analysis, we usually calculate the eigenvectors for a correlation or covariance matrix. Eigenvectors are the directions along which a particular linear transformation acts by flipping, compressing or stretching.

*Eigenvalue* can be referred to as the strength of the transformation in the direction of eigenvector or the factor by which the compression occurs.