The purpose of this book is to provide the reader with a solid background and understanding of the basic results and methods in probability theยญ ory before entering into more advanced courses (in probability and/or statistics). The presentation is fairly thorough and detailed with many solved examples. Several examples are solved with different methods in order to illustrate their different levels of sophistication, their pros, and their cons. The motivation for this style of exposition is that experiยญ ence has proved that the hard part in courses of this kind usually in the application of the results and methods; to know how, when, and where to apply what; and then, technically, to solve a given problem once one knows how to proceed. Exercises are spread out along the way, and every chapter ends with a large selection of problems. Chapters I through VI focus on some central areas of what might be called pure probability theory: multivariate random variables, condiยญ tioning, transforms, order variables, the multivariate normal distribution, and convergence. A final chapter is devoted to the Poisson process beยญ cause of its fundamental role in the theory of stochastic processes, but also because it provides an excellent application of the results and methยญ ods acquired earlier in the book. As an extra bonus, several facts about this process, which are frequently more or less taken for granted, are thereby properly verified
CONTENT
I. Multivariate Random Variables -- II. Conditioning -- III. Transforms -- IV. Order Statistics -- V. The Multivariate Normal Distribution -- VI. Convergence -- VII. The Poisson Process -- Appendixes -- 1. Suggestions for Further Reading -- 2. Some Distributions and Their Characteristics -- 3. Answers to Problems
