The purpose of this book is to provide the reader with a solid background and understanding of the basic results and methods in probability theory before entering into more advanced courses. The first six chapters focus on the central areas of probability; multivariate random variables, conditioning, transforms, order variables, the multivariate normal distribution, and convergence. A final chapter is devoted to the Poisson process as a means to both introduce stochastic processes, and to apply many of the techniques introduced earlier in the text. Students are assumed to have taken a first course in probability though no knowledge of measure theory is assumed. Throughout, the presentation is thorough and includes many examples which are discussed in detail. Thus students considering more advanced research in probability will benefit from this wide-ranging survey of the subject which provides them with a foretaste of the subject's many treasures.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
This book covers the basic results and methods in probability theory. This new edition offers updated content, 100 additional problems for solution, and a new chapter glimpsing further topics such as stable distributions, domains of attraction and martingales.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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