(1 point) Consider a simple model that predicts whether you pass your next test or not based on the result of your previous test.
If you pass your previous test, then you have 0.6 chance you will pass your upcoming test. If you fail your previous test, then you have 0.2 change you will fail your upcoming test. If it continues over a long time, what is the probability that you will pass a test?
I know that I should use eigenvector = 1 and the relationship Ax=A.
I have the matrix [ 0.6 , 0.4],[0.2,0.8]
If I subtract lambda=1 along the diagonal I get,
[-0.4,0.4][0.2,-0.8]*[ Pass, Fail] = [pass, fail]
How do I find the [pass,fail] vector?