Real analysis and probability

Cover; Half-title; Series-title; Title; Copyright; Contents; Preface to the Cambridge Edition; 1 Foundations; Set Theory; 2 General Topology; 3 Measures; 4 Integration; 5 L Spaces; Introduction to Functional Analysis; 6 Convex Sets and Duality of Normed Spaces; 7 Measure, Topology, and Differentiation; 8 Introduction to Probability Theory; 9 Convergence of Laws and Central Limit Theorems; 10 Conditional Expectations and Martingales; 11 Convergence of Laws on Separable Metric Spaces; 12 Stochastic Processes; 13 Measurability; A Axiomatic Set Theory.
This classic graduate textbook offers a clear exposition of modern probability theory and of the interplay between the properties of metric spaces and probability measures The comprehensive historical notes have been further amplified for this new edition, and a number of new exercises have been added, together with hints for solution.