This book covers inequalities, characteristic functions and convergence, the law of large numbers, the central limit theorem and the law of the iterated logarithm. This revised edition updates core material, and offers scores of new problems and exercises.
This book covers inequalities, characteristic functions and convergence, the law of large numbers, the central limit theorem and the law of the iterat...
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 (in probability and/or statistics). The presentation is fairly thorough and detailed with many solved examples. Several examples are solved with di erent methods in order to illustrate their di erent levels of sophistication, their pros, and their cons. The motivation for this style of exposition is that experience has proved that the hard part in courses of this kind usually is the application of the...
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 bef...
Like its predecessor, this book starts from the premise that, rather than being a purely mathematical discipline, probability theory is an intimate companion of statistics. The book starts with the basic tools, and goes on to cover a number of subjects in detail, including chapters on inequalities, characteristic functions and convergence. This is followed by a thorough treatment of the three main subjects in probability theory: the law of large numbers, the central limit theorem, and the law of the iterated logarithm. After a discussion of generalizations and extensions, the book concludes...
Like its predecessor, this book starts from the premise that, rather than being a purely mathematical discipline, probability theory is an intimate co...
