Find the vector of stable probabilities for the Markov
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- 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.Draw the state diagram for the Markov Model and show the transition probabilities on the diagram.If she made the last free throw, then her probability of making the next one is 0.7. On the other hand, If she missed the last free throw, then her probability of making the next one is 0.2. Assume that state 1 is Makes the Free Throw and that state 2 is Misses the Free Throw. (1) Find the transition matrix for this Markov process. P =
- Show how to tind the exact values of the Steady-state probability vector the transit ion matrix 0.8 0.5 0.2 0.5Consider a continuous-time Markov chain with transition rate matrix 0 2 31 Q10 3 2 0/ What are the one-step transition probability matrix of the embedded chain? Enter your answer as a vector of the form ((a₁, b₁, ₁), (a₂, b₂, ₂), (as, bs, cs)) where each of a, b, c, is an integer of the form or a fraction of the form m/n; eg ((1, 1/2, 1/3), (1, 1/2, 1/3), (1, 1/2, 1/3)). Note that there are 8 brackets and 8 commas in total. All should be included. Do not include spaces.3. Markov Chain Representation Describe a situation from your experience and represent it as a Markov chain. Make sure to explciitly specify both the states and the state-transition probabilities.
- PLEASE HELP ME GET THE ANSWER FOR PART B AND IT HAS TO BE FRACTION/INTEGER/ OR EXACT DECIMAL AND THE ASWER I GOT 0.66 FOR FIRST AND 0.99 FOR SECOND AND BOTHER WERE WRONG. The computer center at Rockbottom University has been experiencing computer downtime. Let us assume that the trials of an associated Markov process are defined as one-hour periods and that the probability of the system being in a running state or a down state is based on the state of the system in the previous period. Historical data show the following transition probabilities. To From Running Down Running 0.90 0.10 Down 0.20 0.80 (a) If the system is initially running, what is the probability of the system being down in the next hour of operation? ANSWER FOR PART A IS 0.10 (b) What are the steady-state probabilities of the system being in the running state and in the down state? (Enter your probabilities as fractions.) Running?1= Your answer must be a fraction, integer, or exact decimal. .66 IS…How the markov matrix works? Please provide me a brief explanation with zero Plag*arismIn a city, a study has disclosed that the relationships between the occurrences of a dry day and a wet day in December. From the historical records, the study has shown that the probabilities of a dry day following a dry day and a wet day are 0.95 and 0.70, respectively, in December. Consider a 2-state first order Markov chain for a sequence of dry and wet days. Generate the transitional probability matrix for the relationships between dry and wet days in December. Determine the numbers of dry days and wet days in December over a long period.