1.       

Title of the discipline (basic disciplines)

BASES OF THEORY OF PROBABILITY AND MATHEMATICAL STATISTICS

2.       

Course of Study

Course 1, specialty Mathematics (research and development activities)

3.       

Semester of training
(for each semester a separate table)

2

4.       

Amount of credits
(academic plan)

2

5.       

Full name of the lecturer

Stashulenok Sergei Pavlovich

6.       

Objectives of studying the discipline

Create a knowledge base of students in the field of probability theory and mathematical statistics acquaint students with the basic principles of probability theory and examples of their applications further formation of students’ skills in abstract mathematical thinking and the ability to apply it in specific tasks, enhancing their mathematical culture
As a result of studying the discipline, the student must
know:
 basic concepts of probability theory;-
 basic mathematical models of random phenomena;-
be able to:

 use the basic laws of random phenomena;-
to apply methods of probability theory in other sciences

7.       

Prerequisites

Algebra,
Analytic geometry,
Mathematical analysis

8.       

Contents of the discipline

  Theme  1. CONCEPT OF PROBABILITY

Terminology of probability theory. The subject and problems of probability theory. Events, operations on events. Classical and geometric definitions of probability.

The concept of Kolmogorov’s axiomatics. Probability properties.

Examples of probability spaces. Classical, finite, discrete probability spaces. Geometric probability space, the Bertrand paradox. Statistical probability and frequency stability.

Theme 2. INDEPENDENCE

Conditional probability. Definition of conditional probability. Multiplication theorems. The formula of full probability and Bayesian formula.

 Independence of events. Determining the independence of two events and independence in the aggregate of several events.

 Independent testing. Bernoulli scheme

Theme 3. RANDOM VALUES

Random variables. Classification of random variables. Distributions: binomial, geometric, Poisson, uniform, normal, exponential, chi-square, Cauchy, etc. Function and density of distribution.

 The concept of independence of random variables.

Mathematical expectation and variance, their properties. Inequalities of Chebyshev.

Theme 4. Limit Theorems

The concept of the law of large numbers and the central limit theorem (in the overview order).

Theme 5. ELEMENTS OF MATHEMATICAL STATISTICS

The subject and tasks of mathematical statistics.

Basic concepts of the sampling theory: sample, variation series, histogram, frequency range, empirical distribution function.

9.       

Recommended literature

Main literature:

1. Borovkov AA Probability Theory. M .: Nauka, 1986.
2. Wentzel A.D. Course of the theory of random processes. – Moscow: Nauka, 1978.
3. Gikhman II, Skorokhod AV, Yadrenko MI Theory of Probability and Mathematical Statistics. Kiev: Vishcha Shk., 1979.
4. Gnedenko B. V. Course of the theory of probability. Moscow: Nauka, 1988.
5 Zuev M., Sechko Vl.  Probability Theory i mathematical statistics. Mozyr: White Wind 2000.6. Ivchenko GI, Medvedev Yu. I. Mathematical statistics. М.: Vysch. shk., 1984.
7. Lazakovich NV, Stashulenok SP, Yablonsky O.L. Theory of Probability: A Textbook. – 3rd ed., With modified. – Minsk: BSU, 2013.
8. Rozanov Yu. A. The theory of probability, random processes, mathematical statistics. Moscow: Nauka, 1985.
9. Sevastyanov BA Course of the theory of probability and mathematical statistics. Moscow: Nauka, 1982.
10. Chistyakov VP Course of the theory of probability. M .: Nauka, 1987.
11. Shiryaev AN Probability. M .: Nauka, 1989.

Additional literature:

12. Bolshev LN, Smirnov NV Tables of mathematical statistics. Moscow: Nauka, 1983.
13. AN Kolmogorov, Basic concepts of the theory of probability. Moscow: Nauka, 1974.
14. Kramer G. Mathematical methods of statistics. Moscow: The World, 1976.
15. VM Kruglov. Additional chapters of the theory of probability. М: Vysch. shk., 1984.
16. Lazakovich NV, Stashulenok SP, Yablonsky O.L. Course of probability theory: an electronic textbook. – Minsk: E-book of the Belarusian State University, 2003.
17. Leman E. Testing of statistical hypotheses. Moscow: Nauka, 1964.
18. Partasarati K. Introduction to probability theory and measure theory. Moscow: Mir, 1983.
19. Feller V. Introduction to the theory of probability and its applications. М .: Мир, 1984.Т.1,2.
20. PA Henneken and A. Tortra, Theory of Probability and some of its applications. Moscow: Nauka, 1974.

 Collected problems on the discipline “Theory of Probability and Mathematical Statistics”:

21. Zhdanovich VF, Lazakovich NV Radyno N.Ya. Tasks for laboratory work on the course of probability theory and mathematical statistics in two parts. Part 1. Minsk, 1998.
22. Zhdanovich VF, Lazakovich N.V. Radyno N.Ya., Stashulenok S.P. Tasks for laboratory work on the course of probability theory and mathematical statistics in two parts. Part 2. Minsk, 1999.
23. Meshalkin L.D. A collection of problems in probability theory. M: MSU, 1963.
24. Prokhorov AV, Ushakov VG, Ushakov NG Problems on the theory of probability: Basic concepts. Limit theorems. Random processes. M: Science, 1986.
25. Sevastyanov BA, Chistyakov VP, Zubkov AM Collection of problems in probability theory. M: Science, 1989.
26. Theory of Probability: a Workshop: Textbook. allowance for university students. specialist. : at 2 pm Part 1 / [aut .: NV Lazakovich, EM Radyno, SP Stashulenok, SL Shtin, O.L. Yablonsky]; Ed. NV Lazakovich. – Minsk: BSU, 2011. – 147 p.
27. Theory of Probability: a Workshop: Textbook. allowance for university students. specialist. : at 2 pm Part 2 / [aut .: NV Lazakovich, EM Radyno, SP Stashulenok, A. G. Yablonskaya, O.L. Yablonsky]; Ed. NV Lazakovich. – Minsk: BSU, 2014.- 175s.

References:

28. Prokhorov Yu.V., Rozanov Yu.A. Probability theory. М .: Science, 1973
29. A handbook on probability theory and mathematical statistics. Korolyuk VS, Portenko NI, Skorokhod AV, Turbin AF.  Moscow: Nauka, 1985.

10.   

Teaching Methods

interactive methods of teaching (working in small groups (team), problem training) are organized taking into account the inclusion in the learning process of all students of the group. Joint activity means that each student makes his own individual contribution, in the course of the work there is an exchange of knowledge, ideas, methods of activity. Organized individual, steam and group work. Interactive methods are based on the principles of interaction, activity of trainees, reliance on group experience, mandatory feedback

11.   

Language of instruction

Russian

12.   

Conditions (requirements), routine monitoring

– testing;
– test;
– Colloquium
The score on the exam is set taking into account:
30% – work in laboratory and practical classes, 70% – oral examination

–

13.   

Appraisal Form

Exam