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The Markov process is most commonly known as the Markoff process. It is the natural stochastic process that is followed to satisfy a distinct property called as Markov property. It is named after the Great Russian Mathematician, Andrey Markov.
It is a random process in which the future is independent of the past, i.e. the condition of the present, future, and past are not dependent on each other. The simple class of Markov processes is the Markov Chains. It is defined by the following properties:
Markov Processes are very advanced concepts in statistics. Our proficient experts have a very sound knowledge of all the concepts to fulfill all your requirements regarding the assignments. They are always available to assist and guide the students regarding their assignments.
Markov processes is a very interesting topic whose concepts are used in various subjects like economics, finance, sports, music, etc.
It is one of the toughest topics in statistics that many students face difficulty in understanding and that result in their low grades.
Markov analysis is a method that is adopted to examine the behaviour of the variable available in the project at present or determine the behaviour in the future. This method is usually used in making different decisions. It is also used by various businesses to improve their efficiency.
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