Chapters 1 and 2 deal with basic ideas of probability theory, In Chapter 1 an axiomatic framework is presented, while in Chapter 2 the important concept of a random variable is introduced.(概率，随机变量)
Chapter 3 is concerned with the subject matter of conditional probability and conditional expectation.(条件概率，条件期望)
In Chapter 4 we come into contact with our first random, or stochastic, process, known as a Markov chain, which is widely applicable to the study of many real-world phenomena.(马尔科夫链)
In Chapter 5 we are concerned with a type of stochastic process known as a counting process(Poisson process).(泊松过程，指数分布)
Chapter 6 considers Markov chains in continuous time with an emphasis on birth and death models.(连续时间马尔科夫链)
Chapter 7, the renewal theory chapter, is concerned with a type of counting process more general than the Poisson
Chapter 8 deals with queueing, or waiting line, theory.(排队论)
Chapter 9 is concerned with reliability theory.
Chapter 10 is concerned with Brownian motion and its applications(布朗运动)
Chapter 11 deals with simulation, a powerful tool for analyzing stochastic models that are analytically intractable.(仿真)
