Let P = 0.50.30.50.7 be the transition matrix for a Markov chain with two states. Let x0 = 0.50.5 be the initial state vector for the population. Find the steady state vector x. (Give the steady state vector as a probability vector.)

Probability distribution vector =

Step-By-Step Explanation

If  is the transition matrix for a Markov chain with two states.  

 be the initial state vector for the population.

In the long run, the probability distribution vector Xm approaches the probability distribution vector .

This is called the steady-state (or limiting,) distribution vector.

you need to show us the graph.

step-by-step explanation:

the largest number of the four options is 1.8 x 10-2

you have it in scientific notation.

1.80 x 10-6   = 0.00000180

1.80 x 10-4   = 0.000180 (bigger, or "less small", than the former one)

so

1.8 x 10-2       = 0.0180. as you see. the "less small", or the biggest one of them all.

as you have negative exponent, it means you are dividing 1.8 by 100 (i.e. moving the dot towards left, two times).

if you had positive exponent for the scientific notation, power of tenths, you would be multiplying times 100 (moving the dot towards right) as below:

1.8 x (10)2 = 180

so. if you have negative exponent in scientific notation, move the dot toward left. if it is positive, toward right as many times the exponent tells you.