(i) If volume is high this week, then next week it will be high with a probability of 0.6 and low with a probability of 0.4.(ii) If volume is low this week then it will be high next week with a probability of 0.1.Assume that state 1 is high volume and that state 2 is low volume(1) Find the transition matrix for this Markov process.(2) If the volume this week is high, what is the probability that the volume will be high two weeks from now?(3) What is the probability that volume will be high for three consecutive weeks?

Given information thatVolume is high, the next week it will be high probability 0.6 and low…

Answered: (i) If volume is high this week, then…

Elementary Linear Algebra (MindTap Course List)

8th Edition

ISBN:9781305658004

Author:Ron Larson

Publisher:Ron Larson

Chapter2: Matrices

Section2.5: Markov Chain

Problem 47E: Explain how you can determine the steady state matrix X of an absorbing Markov chain by inspection.

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12. Robots have been programmed to traverse the maze shown in Figure 3.28 and at each junction randomly choose which way to go. Figure 3.28 (a) Construct the transition matrix for the Markov chain that models this situation. (b) Suppose we start with 15 robots at each junction. Find the steady state distribution of robots. (Assume that it takes each robot the same amount of time to travel between two adjacent junctions.)
(i) If volume is high this week, then next week it will be high with a probability of 0.6 and low with a probability of 0.4.(ii) If volume is low this week then it will be high next week with a probability of 0.5.Assume that state 1 is high volume and that state 2 is low volume.(1) Find the transition matrix for this Markov process. (2) If the volume this week is high, what is the probability that the volume will be high two weeks from now? (3) What is the probability that volume will be high for three consecutive weeks?
please explain steps to solve for each question
Suppose that the probability that tomorrow will be a wet day is 0.662 if today is wet and 0.250 if today is dry. The probability that tomorrow will be a dry day is 0.750 if today is dry and 0.338 if today is wet (a) Write down the transition matrix for this Markov chain. (b) If Monday is a dry day, what is the probability that Wednesday will be wet? ( c) In the long run, what will the distribution of wet and dry days be?
(i) If volume is high this week, then next week it will be high with a probability of 0.6 and low with a probability of 0.4. (ii) If volume is low this week then it will be high next week with a probability of 0.2. Assume that state 1 is high volume and that state 2 is low volume. (1) Find the transition matrix for this Markov process. P= (2) If the volume this week is high, what is the probability that the volume will be high two weeks from now? (3) What is the probability that volume will be high for three consecutive weeks?
Solve about the nervous basketball player, using the following data:
A factory worker will quit with probability 1/2 during her first month, with probability 1/4 during her second month and with probability 1/8 after that. Whenever someone quits, their replacement will start at the beginning of the next month. Model the status of each position as a Markov chain with 3 states. Identify the states and transition matrix. Write down the system of equations determining the long-run proportions. Suppose there are 900 workers in the factory. Find the average number of the workers who have been there for more than 2 months.
Please find the transition matrix for this Markov process
If the animal is in the woods on one observation, then it is four times as likely to be in the woods as the meadows on the next observation. If the animal is in the meadows on one observation, then it is three times as likely to be in the meadows as the woods on the next observation. Assume that state 1 is being in the meadows and that state 2 is being in the woods. (1) Find the transition matrix for this Markov process. ... ... P = (2) If the animal is initially in the woods, what is the probability that it is in the woods on the next three observations? (3) If the animal is initially in the woods, what is the probability that it is in the meadow on the next three observations?
An individual can contract a particular disease with probability 0.17. A sick person will recover dur- ing any particular time period with probability 0.44 (in which case they will be considered healthy at the beginning of the next time period). Assume that people do not develop resistance, so that pre- vious sickness does not influence the chances of contracting the disease again. Model as a Markov chain, give transition matrix on your paper. Find the probability that a healthy individual will be sick after two time periods.
A system consists of five components, each can be operational or not. Each day one operational component is used and it will fail with probability 20%. Suppose there are five repairmen available that can each work on one broken down component per day. Each repairman successfully fixes the component with probability 70% regardless of whether he has worked on it previous days. Model the system as a Markov chain Write down equations for determining long-run proportions. Suppose that you are interested in the average number of repairmen who are working per day. Explain how you would find it using your model. You are not asked to solve any equations here, instead describe how you would use the solutions.
Please show solutions and explain steps

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