5. South Bend weather, as follows: (1) If the last two days have been sunny, then 95% of the time, tomorrow will be sunny. (2) If yesterday was rainy and today is sunny, then 80% of the time, tomorrow will be sunny. (3) If yesterday was sunny and today is rainy, then 60% of the time, tomorrow will be rainy. (4) If the last two days have been rainy, then 75% of the time, tomorrow will be rainy. Using this information, (a) Model South Bend's weather as a Markov chain by giving a transition probability matrix. (b) Draw the state transition diagram for this Markov chain. (c) If tomorrow's weather depends on the last three days of South Bend weather, how many states will be needed to model the weather as a Markov chain? And what are the possible states?

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5. South Bend weather, as follows:
(1) If the last two days have been sunny, then 95% of the time, tomorrow will be sunny.
(2) If yesterday was rainy and today is sunny, then 80% of the time, tomorrow will be sunny.
(3) If yesterday was sunny and today is rainy, then 60% of the time, tomorrow will be rainy.
(4) If the last two days have been rainy, then 75% of the time, tomorrow will be rainy.
Using this information,
(a) Model South Bend's weather as a Markov chain by giving a transition probability matrix.
(b) Draw the state transition diagram for this Markov chain.
(c) If tomorrow's weather depends on the last three days of South Bend weather, how many states will be
needed to model the weather as a Markov chain? And what are the possible states?
Transcribed Image Text:5. South Bend weather, as follows: (1) If the last two days have been sunny, then 95% of the time, tomorrow will be sunny. (2) If yesterday was rainy and today is sunny, then 80% of the time, tomorrow will be sunny. (3) If yesterday was sunny and today is rainy, then 60% of the time, tomorrow will be rainy. (4) If the last two days have been rainy, then 75% of the time, tomorrow will be rainy. Using this information, (a) Model South Bend's weather as a Markov chain by giving a transition probability matrix. (b) Draw the state transition diagram for this Markov chain. (c) If tomorrow's weather depends on the last three days of South Bend weather, how many states will be needed to model the weather as a Markov chain? And what are the possible states?
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