| I. RANDOM EVENTS |
| 1. Relations among random events |
| 2. A direct method for evaluating probabilities |
| 3. Geometric probabilities |
| 4. Conditonal probability. The multiplication theorem for probabilities |
| 5. The addition theorem for probabilities |
| 6. The total probability formula |
| 7. Computation of the probabilities of hypotheses after a trial (Bayes' formula) |
| 8. Evaluation of probabilities of occurrence of an event in repeated independent trials |
| 9. The multinomial distribution. Recursion formulas. Generating functions |
| II. RANDOM VARIABLES |
| 10. "The probability distribution series, the distribution polygon and the distribution function of a discrete random variable" |
| 11. The distribution function and the probability density function of a continuous random variable |
| 12. Numerical characteristics of discrete random variables |
| 13. Numerical characteristics of continuous random variables |
| 14. Poisson's law |
| 15. The normal distribution law |
| 16. Characteristic functions |
| 17. The computation of the total probability and the probability density in terms of conditional probability |
| III. SYSTEMS OF RANDOM VARIABLES |
| 18. Distribution laws and numerical characteristics of systems of random variables |
| 19. The normal distribution law in the plane and in space. The multidimensional normal distribution |
| 20. Distribution laws of subsystems of continuous random variables and conditional distribution laws |
| IV. NUMERICAL CHARACTERISTICS AND DISTRIBUTION LAWS OF FUNCTIONS OF RANDOM VARIABLES |
| 21. Numerical characteristics of functions of random variables |
| 22. The distribution laws of functions of random variables |
| 23. The characteristic functions of systems and functions of random variables |
| 24. Convolution of distribution laws |
| 25. The linearization of functions of random variables |
| 26. The convolution of two-dimensional and three-dimensional normal distribution laws by use of the notion of deviation vectors |
| V. ENTROPY AND INFORMATION |
| 27. The entropy of random events and variables |
| 28. The quantity of information |
| VI. THE LIMIT THEOREMS |
| 29. The law of large numbers |
| 30. The de Moivre-Laplace and Lyapunov theorems |
| VII. THE CORRELATION THEORY OF RANDOM FUNCTIONS |
| 31. General properties of correlation functions and distribution laws of random functions |
| 32. Linear operations with random functions |
| 33. Problems on passages |
| 34. Spectral decomposition of stationary random functions |
| 35. Computation of probability characteristics of random functions at the output of dynamical systems |
| 36. Optimal dynamical systems |
| 37. The method of envelopes |
| VIII. MARKOV PROCESSES |
| 38. Markov chains |
| 39. The Markov processes with a discrete number of states |
| 40. Continuous Markov proc |
| IX. METHODS OF DATA PROCESSNG |
| 41. Determination of the moments of random variables from experimental data |
| 42. Confidence levels and confidence intervals |
| 43. Tests of goodness-of-fit |
| 44. Data processing by the method of least squares |
| 45. Statistical methods of quality control |
| 46. Determination of probability characteristics of random functions from experimental data |
| ANSWERS AND SOLUTIONS |
| SOURCES OF TABLES REFERRED TO IN THE TEXT |
| BIBLIOGRAPHY |
| INDEX |