4:20 If A is singular then $\lambda=0$ is an eigenvalue15:00 An nxn matrix will have n eigenvalues and the tr(A) will be the sum of the eigenvalues19:30 “A repeated lambda is the source of all trouble in 18.06”25:00 Shows the polynomial contains the trace and the determinant, in the 2x2 case.37:15  Example: Rotate vector by 90 degrees38:47 The determinant is the product of the eigenvalues.44:20 If we stick to symmetric matrices, or close to symmetric, then the eigenvalues will stay real.46:50 With a triangular matrix, we can read the eigenvalues off of the diagonal####[]