This clear exposition begins with basic concepts and moves on to combination of events, dependent events and random variables, Bernoulli trials and the De Moivre-Laplace theorem, a detailed treatment of Markov chains, continuous Markov processes, and more. Includes 150 problems, many with answers. Indispensable to mathematicians and natural scientists alike. |

"It is amazing that a 148 page book can cover so much with such clarity. Even more amazing is the way it covers all basics, going from combinatorial problems to limit theorems in the first half, with a measure of relevant examples and a good selection of problems. It makes an equally excellent choice of "additional topics": Markov chains and processes, information theory, game theory, branching processes, and optimal control.
This book is not for everyone, as it does require a small degree of mathematical sophistication. But it will prove most useful for a very large audience. For serious beginning mathematics and science students it will provide the quickest way to learn the subject. For lecturers devising an introductory probability course it will make an excellent textbook. And, most importantly, for mathematicians and scientists of all kinds it will serve as an indispensable concise reference book."
"This is not meant as an introductory text--rather, it's a very handy reference for major concepts needed in probability and stochastic calculus. It was one of the few places where I could find a proof of the DeMoivre-Laplace theorem.
The examples are also very good--they touch upon basic problems in the field without being overly trivial."
"There are quite a number of books offering a quick introduction to the fundamentals of probability. And there is a demand, as these tools have many practical uses: Testing data, sampling, insurance topics, quality checking, finance, investment, and finance, to mention only a few. Rozanov's book, of just a little over 100 pages, helps the novice turning practical problems into numbers. What it does well is letting the beginning student acquire a sense of what the rules are, events, combination of events using the mathematical notions of union and intersection; show how they yield computations with probability, distributions; dependence and independence, repeated experiments; and use of conditional probability. It concludes with limit theorems, Markov chains and Markov processes. There are other nice books that go beyond Rozanov; for example Heathcote's PROBABILITY, also in the Dover series. Review by Palle Jorgensen, August 2008." |