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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 0.70 0.30 Down 0.20 0.80 If the system is initially running, what is the probability of the system being down in the next hour of operation

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User Estefany
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Answer:

The probability of the system being down in the next hour of operation is 0.3.

Explanation:

We have a transition matrix from one period to the next (one hour) that can be written as:


T=\left[\begin{array}{ccc}&R&D\\R&0.7&0.3\\D&0.2&0.8\end{array}\right]

We can represent the state that system is initially running with the vector:


S_0=\left[\begin{array}{cc}1&0\end{array}\right]

The probabilties of the states in the next period can be calculated using the matrix product of the actual state and the transition matrix:


S_1=S_0\cdot T

That is:


S_1=S_0\cdot T= \left[\begin{array}{cc}1&0\end{array}\right]\cdot \left[\begin{array}{cc}0.7&0.3\\0.2&0.8\end{array}\right]= \left[\begin{array}{cc}0.7&0.3\end{array}\right]

With the inital state as running, we have a probabilty of 0.7 that the system will be running in the next hour and a probability of 0.3 that it will be down.

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User Anthony Nandaa
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