Table of Contents

1. Elementary Probabilities.- 1. Combinatorics.- 2. Events and Relations among Them.- 3. Classical Definition of Probability.- 4. Conditional Probability. Independence of Events.- 5. Probability of a Sum of Events. Formula for Total Probability. Bayes’ Formula.- 6. Urn Models. Polya Urn Model.- 7. Geometric Probabilty.- 8. Bernoulli Trials. Binomoal and Multinomial Distributions.- 9. Discrete Random Variables and Their Characteristics.- 10. Normal and Poisson Approximations for the Binomial Distribution.- 2. Probability Spaces and Random Variables.- 11. General Definition of Probability and ?-Algebra of Events.- 12. Random Variables and Integration.- 13. Conditional Probability, Independence and Martingales.- 14. Product of Measurable Spaces and Probabilities on Them.- 3. Characteristics of Random Variables.- 15. Distribution Function.- 16. Multivarite Distributions and Functions of Random Variables.- 17. Expectation, Variance and Moments of Higher Order.- 18. Generating Functions and Characteristic Functions.- 19. Infinitely Divisible and Stable Distributions.- 20. Conditional Distributions and Conditional Expectation.- 21. Inequalities for Random Variables.- 4. Limit Theorems.- 22. Types of Convergence for Sequences of Random Variables.- 23. Laws of Large Numbers.- 24. Central Limit Theorem and Related Topics.- Solutions, Hints, and Answers.- Table 1 (Normal distribution).- Table 2 (Poisson distribution).- References.

Reviews

`The book is very comprehensive and is recommended to anyone interested in the more mathematical aspects of probability theory. It is written with extreme care and will remain one of the basic references in this field for a long time to come. I would say that this is the best book for all those who are interested in pure and applied probability theory.'
Acta Applicandae Mathematicae, 21 (1990)