Titlebook: Basics of Probability and Stochastic Processes; Esra Bas Textbook 2019 Springer Nature Switzerland AG 2019 Markov chains.Random variables.

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A Brief Introduction to Stochastic Processesete-time and continuous-time stochastic process, state space, . stochastic process, stopping time, and the hitting time of a process to a state. Some typical examples and problems including the daily stock prices of a company, and the evolution of the population of a country have been provided to clarify the basic concepts.

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Special Discrete-Time Markov Chainsimple symmetric random walk, Gambler’s ruin problem as a special simple random walk, branching process, hidden Markov chains, time-reversible discrete-time Markov chains, and Markov decision processes. Some illustrative examples and problems have been provided for each special discrete-time Markov chain.

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Springer Tracts in Modern Physicsist of moment generating functions has been provided for special random variables. The last part of the chapter included the limit theorems in probability including Strong Law of Large Numbers and Central Limit Theorem. The concepts have been illustrated with several examples and problems.

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Field and power-dependent surface impedance,dition to the typical example of the arrival of the customers; other illustrative examples including the breakdown of the machines, time of the earthquakes, and the two-server systems have also been presented, and solved by using the basic formulae and the schematic representations.

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Other Selected Topics in Basic Probabilityist of moment generating functions has been provided for special random variables. The last part of the chapter included the limit theorems in probability including Strong Law of Large Numbers and Central Limit Theorem. The concepts have been illustrated with several examples and problems.