Probability Theory and Mathematical Statistics
Course: Computer Systems and Networks Engineering
Structural unit: Faculty of Radiophysics, Electronics and Computer Systems
Title
Probability Theory and Mathematical Statistics
Code
ОК 14
Module type
Обов’язкова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
2 Semester
Number of ECTS credits allocated
4
Learning outcomes
The purpose of the discipline - students mastery of the basic concepts, approaches and methods of probability theory and mathematical statistics, necessary for the study of more special courses, which is the basis for a specialist in programming and modeling.
Form of study
Full-time form
Prerequisites and co-requisites
Before studying the discipline "Probability Theory and Mathematical Statistics" it is necessary to master the subject "Higher Mathematics".
Prerequisites:
the student must know: combinatorics, technique of integration and differentiation, in particular, improper and multiple integrals, series.
the student must be able to: use the mastered methods of "Higher Mathematics" in practice.
Course content
The discipline consists of three parts. The first part is devoted to the basics of probability theory: combinatorics, classical and geometric definition of probabilities, the basic theorems of probability theory. The second part deals with the concept of random variable. Discrete and absolutely continuous random variables and their characteristics are considered. The third part of the course contains an introduction to mathematical statistics and covers such basic methods of constructing statistical estimates as the method of moments and likelihood method, as well as criterion.
Recommended or required reading and other learning resources/tools
1. В.М. Турчин Теорія ймовірностей і математична статистика. Основні поняття, приклади, задачі. – Д.: Вид-во Дніпропетр. нац. ун-ту, 2006.
2. А.Я. Дороговцев, Д.С. Сільвестров, А.В. Скороход, М.Й. Ядренко. Теорія ймовірностей. Збірник задач – К.:Вища школа, 1976.
3. О.М. Радченко. Основи теорії ймовірностей. – К, ВПЦ «Київський університет», 2007.
4. В.В. Михайленко. Теорія ймовірностей, математична статистика та випадкові функції. Курс лекцій: Навчальний посібник. – Житомир:ЖІТІ, 2003.
Planned learning activities and teaching methods
This course provides classes in the amount of: lectures - 30 hours, practical classes - 30 hours; individual work of students in the amount of 86 hours is also planned. Methods of semester control: tests conducted during practical classes and individual homework. Final control is test.
Assessment methods and criteria
The level of achievement of all learning outcomes is determined by the results of written tests. Contribution of learning outcomes to the final assessment:
1.1 - 1.10 [knowledge] - up to 45%; 2.1 - 2.3 [skills] - up to 45%; 3.1-3.2 [communication] - up to 5%; 4.1 [autonomy and responsibility] - up to 5%;
Forms of estimation:
- semester assessment: The academic semester has three modules. The first is rated up to 20 points, the second - up to 25 points, the third - up to 15. Homework is part of the relevant module. Written tests are conducted after the completion of relevant topics. The course includes two current tests and one modul test.
- final assessment (in the form of test): test form - written and oral. The test consists of 1 theoretical question and 4 tasks. Each question and each task is evaluated from 0 to 8 points. In total, you can get from 0 to 40 points for the test.
Language of instruction
Ukranian
Lecturers
This discipline is taught by the following teachers
Olena
Volodymirivna
Sugakova
Department of mathematics and Theoretical Radio Physics
Faculty of Radiophysics, Electronics and Computer Systems
Faculty of Radiophysics, Electronics and Computer Systems
Departments
The following departments are involved in teaching the above discipline
Department of mathematics and Theoretical Radio Physics
Faculty of Radiophysics, Electronics and Computer Systems