| This book is a complete revision of the earlier work Probability which appeared in 1970. While revised so radically and incorporating so much new material as to amount to a new text, it preserves both the aim and the approach of the original. That aim was stated as the provision of a 'first text in probability, demanding a reasonable but not extensive knowledge of mathematics, and taking the reader to what one might describe as a good intermediate level'. In doing so it attempted to break away from stereotyped applications, and consider applications of a more novel and significant character. The particular novelty of the approach was that expectation was taken as the prime concept, and the concept of expectation axiomatized rather than that of a probability measure. In the preface to the original text of 1970 (reproduced below, together with that to the Russian edition of 1982) I listed what I saw as the advantages of the approach in as unlaboured a fashion as I could. I also took the view that the text rather than the author should persuade, and left the text to speak for itself. It has, indeed, stimulated a steady interest, to the point that Springer-Verlag has now commissioned this complete reworking. 本书为英文版。 |
| Preface to the Third Edition Preface to Probability (1970) Preface to the Russian Edition of Probability (1982) CHAPTER1 Uncertainty， Intuition and Expectation 1.Ideas and Examples 2.The Empirical Basis 3.Averages over a Finite Population 4.Repeated Sampling: Expectation 5.More on Sample Spaces and Variables 6.Ideal and Actual Experiments: Observables CHAPTER2 Expectation 1.Random Variables 2.Axioms for the Expectation Operator 3.Events: Probability 4.Some Examples of an Expectation 5.Moments 6.Applications: Optimization Problems 7.Equiprobable Outcomes: Sample Surveys 8.Applications:Least Square Estimation of Random Variables 9.Some Implications of the Axiomx CHAPTER3 Probablility 1.Events,Sets and Indicatiors 2.Probability Measure 3.Expectation as a Probability Integral 4.Some History 5.Subjective Probability CHAPTER4 Some Basic Models 1.A Model of Spatial Distribution 2.The Multinomial,Binomial,Poisson and Geometric Distributions 3.Independence 4.Probability Generating Functions 5.The St.Petersburg Paradox 6.Matching,and Other Combinatorial Problems 7.Conditioning 8.Variables on the Continuum:the Exponential and Gamma Distributions CHAPTER5 Conditioning 1.Conditional Expectation 2.Conditional Probability 3.A Conditional Expectationas a Random Variable 4.Conditioning on a Field 5.Independence 6.Statistical decision Theory 7.Information Transmission 8.Acceptance Sampling CHAPTER6 Applications of the Independence Concept 1.Renewal Processes 2.Recurrent Events:Regeneration Points 3.A Result in Statistical Mechanics:the Gibbs Distribution 4.Branching Processes CHAPTER7 The Two Basic Limit Theorems 1.Convergence in Distribution(Weak Convergence) 2.Properties of the Characteristic Function 3.The Law of Large Numbers 4.Normal Convergence(the Central Limit Theorem) 5.The Normal Distribution CHAPTER8 Continuous Random Variables and Their Transformations 1.Distributions with a Density 2.Functions of Random Variables 3.Conditional Densities CHAPTER9 Markov Processes in Discrete Time 1.Stochastic Processes and the Markov Property …… CHAPTER10 Markov Processes in Continuous Time CHAPTER11 Second-Order Theory CHAPTER12 Consistency and Extension:the Finite-Dimensional Case CHAPTER13 Stochastic Convergence CHAPTER14 Martingales CHAPTER15 Extension:Examples of the Infinite-Dimensional Case CHAPTER16 Some Interesting Processes References Index |
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