Introduction To Probability Book

An intuitive, yet precise introduction to probability theory, stochastic processes, and probabilistic models in science, engineering, and related fields. This second edition includes a thorough introduction to Bayesian and classical statistics. This is the currently used textbook for "Probabilistic Systems Analysis," an introductory probability course at the Massachusetts Institute of Technology, attended by a large number of undergraduate and graduate students. The book covers the fundamentals of probability theory (probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems), which are typically part of a first course on the subject, as well as the fundamental concepts and methods of statistical inference, both Bayesian and classical. It also contains, a number of more advanced topics, from which an instructor can choose to match the goals of a particular course. These topics include transforms, sums of random variables, a fairly detailed introduction to Bernoulli, Poisson, and Markov processes.  The book strikes a balance between simplicity in exposition and sophistication in analytical reasoning. Some of the more mathematically rigorous analysis has been just intuitively explained in the text, but is developed in detail (at the level of advanced calculus) in the numerous solved theoretical problems. The book has been widely adopted for classroom use in introductory probability courses within the USA and abroad. The authors are Professors in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology. They are members of the prestigious US National Academy of Engineering. They have written several widely used textbooks and research monographs. Reviews: Several reviews can be found in the listing of the first edition of this book. Contents, preface, more info, and resources such as intstruction slides, and self-study-exercises, at publisher's website www.athenasc.comRead More