<p><P>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 some central areas of what might be called pure probability theory: mul
An Intermediate Course in Probability
โ Scribed by Allan Gut (auth.)
- Publisher
- Springer New York
- Year
- 1995
- Tongue
- English
- Leaves
- 288
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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.
โฆ Table of Contents
Front Matter....Pages i-xiii
Introduction....Pages 1-16
Multivariate Random Variables....Pages 17-31
Conditioning....Pages 32-59
Transforms....Pages 60-101
Order Statistics....Pages 102-118
The Multivariate Normal Distribution....Pages 119-148
Convergence....Pages 149-194
The Poisson Process....Pages 195-251
Back Matter....Pages 253-278
โฆ Subjects
Statistical Theory and Methods; Probability Theory and Stochastic Processes
๐ SIMILAR VOLUMES
<p><span>An Advanced Course in Probability and Stochastic Processes </span><span>provides a modern and rigorous treatment of probability theory and stochastic processes at an upper undergraduate and graduate level. Starting with the foundations of measure theory, this book introduces the key concept