Chapter 17 Part 1

# Chapter 17 Part 1 - Chapter 17 Markov Processes Part 1...

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Chapter 17 Markov Processes – Part 1

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Markov Processes Markov process models are useful in studying the evolution of systems over repeated trials or sequential time periods or stages. Examples: Brand Loyalty Equipment performance Stock performance
Markov Processes When utilized, they can state the probability of switching from one state to another at a given period of time Examples: The probability that a person buying Colgate this period will purchase Crest next period The probability that a machine that is working properly this period will break down the next period

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Markov Processes A Markov system (or Markov process or Markov chain) is a system that can be in one of several (numbered) states, and can pass from one state to another each time step according to fixed probabilities. If a Markov system is in state i, there is a fixed probability, p ij , of it going into state j the next time step, and p ij is called a transition probability.

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Chapter 17 Part 1 - Chapter 17 Markov Processes Part 1...

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