22. a. If Ax = Ax for some scalar A, then x is an eigenvector of A. b. If V] and V; are linearly independent eigenvectors, then they correspond to distinct eigenvalues. c. A steadystate vector for a stochastic matrix is actually an eigenvector. d. The eigenvalues of a matrix are on its main diagonal. e. An eigenspace of A is a null space of a certain matrix