Let $T:V\to V$ be a linear transformation on a finite-dimensional inner product space $V$.Show that $\lambda$ is an eigenvalue of $T$ if and only if $\bar{\lambda}$ is an eigenvalue of $T^*$.
Proof given:
Let O be an orthonormal basis for V. Then $\lambda$ is an eigenvalue of $T$ if and only if $\lambda$ is an eigenvalue of $[T]_O$ if and only if rank($[T]_O - \lambda I) \geq 1$ if and only if rank($([T]_O - \lambda I)^*) \geq 1$ if and only if rank($[T^*]_O - \bar{\lambda} I) \geq 1$ if and only if $\bar{\lambda}$ is an eigenvalue of $[T^*]_O$ if and only if $\bar{\lambda}$ is an eigenvalue of $T^*$.
My question is why $\lambda$ is an eigenvalue of a matrix, say A if and only if rank$(A- \lambda I) \geq 1$?