In Markov chains, if I was given a transition probability matrix with each of the probabilities specified, then how do I determine the following:1- Probability that state y is visited at least n times given that you start in state x. I know that I can solve it using Px(# of visits to state y ≥ n) = rhoxy(rhoyy)n−1 where rhoxy is the probability that starting at state x, I will be in state y in some positive time (i. e. rhoxy=Px(Ty<[infinity])). But I am not sure how to calculate rhoxy and I have spent so much time trying to figure it out!

Let us imagine that the number of automobile accidents in a certain region are related to the regional number of registered automobiles in tens of thousands (b1), alcoholic beverage sales in $10,000 (b2), and decrease in the price of gasoline in cents (b3). furthermore, imagine that the regression formula has been calculated as: y = a + b1x1 + b2x2 + b3x3 where y = the number of automobile accidents, a = 7.5, b1 = 3.5, b2 = 4.5, and b3 = 2.5 calculate the expected number of automobile accidents for a football weekend if the region has 25,000 registered vehicles, $75,000 worth of beer is sold, and a gas war causes a 10 cent drop in a gallon of gas.