Markov Analysis can be defined as the method used to forecast the value of a variable whose future value is independent of its past history and this technique is named after Russian mathematician Andrei Andreyevich Markov. Andrei Andreyevich Markov initiated his systematic study of stochastic processes which are processes that involve the operation of chance. It makes use of a method for forecasting random variables where the Markov analysis has a number of applications in the business world and the two common applications are in estimating the proportion of a company's accounts receivables which will become bad debts and forecasting future brand loyalty of current customers.

It can be defined as the statistical technique that is mainly used in forecasting the future behavior of a variable or a system. This gives the current state or behavior does not depend on its state or the behavior at any time in the past and in other words, it is random. For example, while flipping a coin, the probability of a coin and the probability of a flip coming up heads is the same regardless of whether the previous result was heads as well as tail. In accounting, it is used in estimating the bad debt or uncollectible. In the case of the marketer, it is used in modeling future brand loyalty of the consumer that is based on their current rate of the purchases as well as the repurchases. In the quality control QC, this method is applicable to a common cause and another sequence that is dependent on events that can handle system degradation.

It provides a means of analyzing the reliability as well as the availability whose components can exhibit strong dependencies. The other analysis methods are the Kinetic Tree Theory method which is utilized within the fault tree analyses that generally assume component independence. This may lead to optimistic predictions for the systems available as well as reliability parameters. Some typical dependencies are handled using Markov models which are the components in cold or warm standby. The other typical dependencies are the common maintenance personnel as well as common spares with limited on-site stock.

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