part a.) Mark the correct statements

Markov chain is defined as a discrete-time, continuous state Markov process

A Markov chain is said to be homogeneous when the transition from i to j (for all i and j) has the same probability at any time.

Credit scores of individuals serve as an example of a Markov process.

According to standard notation, given an X(t) Markov chain, the transition probability pi,j(t) denotes the probability that of the transition from state jto state i at time t.

part b.) Mark the incorrect statements

All Markov chains, as long as they come from discrete time and discrete sate stochastic processes have a steady state.

Any regular Markov chain has a steady-state distribution.

Under the matrix approach, since the transition between states is stochastic, both the sum of each row and the sum of each column totals 1.

Given a Markov transition matrix, a Markov chain is regular if there is an h such that the h-step transition probability matrix P(h) has all non-zero entries.

Under the matrix approach, since the transition between states is stochastic, the sum of transition probabilities of each row totals 1, but this is not true for columns.