Approach your problems from the right end It isn't that they can't see the solution. It is and begin with the answers. Then one day, that they can't see the problem. perhaps you will find the final question. G. K. Chesterton. The Scandal of Father 'The Hermit Clad in Crane Feathers' in R. Brown 'The point of a Pin'. van Gulik's The Chinese Maze Murders. Growing specialization and diversification have brought a host of monographs and textbooks on increasingly specialized topics. However, the "tree" of knowledge of mathematics and related fields does not grow only by putting forth new branches. It also happens, quite often in fact, that branches which were thought to be completely disparate are suddenly seen to be related. Further, the kind and level of sophistication of mathematics applied in various sciences has changed drastically in recent years: measure theory is used (non-trivially) in regional and theoretical economics; algebraic geometry interacts with physics; the Minkowsky lemma, coding theory and the structure of water meet one another in packing and covering theory; quantum fields, crystal defects and mathematical programming profit from homotopy theory; Lie algebras are relevant to filtering; and prediction and electrical engineering can use Stein spaces. And in addition to this there are such new emerging subdisciplines as "experimental mathematics", "CFD", "completely integrable systems", "chaos, synergetics and large-scale order", which are almost impossible to fit into the existing classification schemes. They draw upon widely different sections of mathematics.

Inhalt

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.