Written by one of the best-known probabilists in the world this text offers a clear and modern presentation of modern probability theory and an exposition of the interplay between the properties of metric spaces and those of probability measures. This text is the first at this level to include discussions of the subadditive ergodic theorems, metrics for convergence in laws and the Borel isomorphism theory. The proofs for the theorems are consistently brief and clear and each chapter concludes with a set of historical notes and references. This book should be of interest to students taking degree courses in real analysis and/or probability theory.
Students and theorists across fields as diverse as real analysis, probability, statistics, and engineering will want a copy of this book.
The first part of the book systematically presents concepts and results from analysis before embarking on the study of probability theory.
Real Analysis and Probability
An Introduction to the Theory of Real Functions and Integration Jewgeni H. Dshalalow. Series Editor STEVEN G. KRANTZ ... Operators on Spaces of Analytic Functions John P. D'Angelo, Several Complex Variables and the Geometry of Real ...
This new edition of the widely used analysis book continues to cover real analysis in greater detail and at a more advanced level than most books on the subject.
Motivated by a brief review of Riemann integration and its deficiencies, the text begins by immersing students in the concepts of measure and integration.
This book will be an indispensable resource in courses on mathematics for economists and as a reference for graduate students working on economic theory.
This famous little book remains a foundational text for the understanding of probability theory, important both to students beginning a serious study of probability and to historians of modern mathematics. 1956 second edition.
A text for a first graduate course in real analysis for students in pure and applied mathematics, statistics, education, engineering, and economics.
Probability and Mathematical Statistics: An Introduction provides a well-balanced first introduction to probability theory and mathematical statistics. This book is organized into two sections encompassing nine chapters.