00:01
We consider a discrete time markov chain with the transition probability matrix shown here and we're asked if it is known that the process is in state 2 so this row represents state 2 at time 205 calculate the probability of the process will be in state 4 at time 207 so in the transition matrix each row the first row represents being in state 1 the second row represents being in state 2 third row being in state 3 and so on.
00:46
And for a given state, different columns represent the probabilities of being in other states after one transition.
00:58
So if we're in state 1, there's a probability of 1 of remaining in state 1.
01:03
So that means you're stuck in state 1.
01:06
If we're in state 2, there's a 0 .2 probability of moving into state 1, a 0 .3 probability of moving into state 2, a 0 .1 probability moving into state 3 and so on.
01:17
So we know we're in state 2 at time 205.
01:21
What is the probability we're at state 4 at time 207? so we either transition to some other state or remain in state 2 at time 206 and then one more transition later to time 207.
01:36
What is the probability that we end up in state 4? so the probability of going from state 1 to state 4 is 0 so that means we we don't have to look at the pathway that goes through state 1 at time 206, because we know the probability of going to state 4 from there is 0...