Reference no: EM132204763

1. A state condition where-as the probability of one event changes as a result of occurrence of another related event is known as:

1. initial probability

2. transition matrix

3. stationary probability

4. conditional probability

2. The steady state probabilities of a double stochastic probability matrix is equal to

1. 1.0

2. 1/(m*n), where m is the number of rows of the matrix and n is the number of columns of the matrix

3. 1/n, where n is the number of columns in the matrix

4. 0.50

5. None of the above

3. The Markov state where, in all conditions, it will never converge to steady state is

1. Periodic State

2. Absorbing State

3. Ergodic State

4. Trapping State

5. Transient

4. Match the term with the associtated definition

Stochastic Process

Time

State

Transition

A. A random variable, {X(t)}, where t is a time index that takes values from a given set T. T may be discrete or continuous

B. A vector that describes attributes of a system at any point in time.

C. A function that determines the next state, s', based on the current state, s, and the event, x. Also known as the Transition Matrix

D. The parameter of a stochastic process.