Answer:
Step-by-step explanation:
Consider the matrix [tex]\begin{matrix} 1 & -2 \\ 2 & 5 \end{matrix} [/tex]. We will calculate the correspondent eigenvalues and eigen vector of the matrix. REcall that, to calculate the eigenvalues of a square matrix A, we must solve the following equation [tex]\text{det}(A-\lambda I ) =0[/tex] where I is the identity matrix. In this case we have the following
[tex]\text{det}\left(\begin{matrix} 1-\lambda & -2 \\ 2 & 5-\lambda \end{matrix}\right) = [/tex]
which gives us the following polynomial (known as the characteristic polynomial of the matrix A).
[tex](1-\lambda)(5-\lambda)+4 =0 = \lambda^2-6\lambda + 9 = (\lambda -3)^2[/tex].
Hence, the only eigenvalue of the given matrix is [tex]\lambda = 3[/tex].
For us to calculate the eigenvalue, we want to find a base for the Kernel of matrix [tex]A-\lambda I[/tex] replacing the value of lambda with the value of the eigen value. REcall that finding the base for the Kernel is solving the associated homogeneus system of the matrix
[tex]\left[\begin{matrix} -2 & -2 \\ 2 & 2 \end{matrix}\right]= \left[\begin{matrix} 0 \\ 0 \end{matrix}\right][/tex]
which lead us to the equation [tex]-2x-2y=0[/tex] or equivalently, [tex]y=-x[/tex]. Hence, the solution of the system is of the form (x,y) = (x,-x) = x(1,-1). So the correspondent eigenvector is the vector (1,-1).