Probability Theory for Economists

Course: Economic Cybernetics

Structural unit: Faculty of Economics

Title
Probability Theory for Economists
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
5
Learning outcomes
PLO 8. Apply appropriate economic-mathematical methods and models to solve economic problems. PLO 12. Apply the acquired theoretical knowledge to solve practical tasks and meaningfully interpret the obtained results. PLO 21. Be able to think abstractly, apply analysis and synthesis to identify key characteristics of economic systems of different levels, as well as specifics of their subjects’ behavior.
Form of study
Full-time form
Prerequisites and co-requisites
1. Know the basic concepts of the theory of boundaries of sequences and functions, the concept of differentiation and integration of a function of one variable. 2. Have the skills to differentiate and integrate the functions of one variable, the application of derivatives to the study of functions.
Course content
The curriculum consists of the following content modules: Content module 1. "Random events and their probabilities. Random quantities and distribution functions ", which discusses the basic concepts of probability theory, axioms of probability theory, discrete random variables, continuous random variables, numerical characteristics of random variables; Content module 2. "Sequences of random variables. Boundary theorems of probability theory. Elements of the theory of random processes-1 ", which considers the limit theorems of probability theory: the law of large numbers, the central limit theorem; characteristic functions, discrete Markov chains, ergodic theorem for discrete Markov chains, basic types of random processes, processes with independent increments, Wiener process, reduction processes, branching processes.
Recommended or required reading and other learning resources/tools
Черняк О.І., Обушна О.М.,Ставицький А.В. Теорія ймовірностей та математична статистика. Збірник задач. – К.:Знання, 2002. Черняк О.І., Ляшенко О.І., Кравець Т.В., Банна О.Л. Теорія ймовірностей та математична статистика. Практикум.- Тернопіль: Економічна думка, 2019. Барковський В. В., Барковська Н. В., Лопатін О. К. Теорія ймовірностей та математична статистика. Підручник– К. : Центр учбової літератури, 2019. Кармелюк Г.І. Теорія ймовірностей та математична статистика. Посібник з розв’язування задач: Навч. посібник.– К.: Центр учбової літератури, 2019. Жлуктенко В.І., Наконечний С.І. Теорія ймовірностей і математична статистика: Навч.-метод.посібник. У 2ч. – Ч.І. Теорія ймовірностей. – К.: КНЕУ, 2007. Черняк О.І., Кравець Т.В., Банна О.Л., Полосьмак О.Л. Теорія ймовірностей та математична статистика: навчально-методичний комплекс для студентів економічних спеціальностей денної та заочної форми навчання. Ч.1. Теорія ймовірностей.- К.: ВПЦ „Київський університет”, 2013.
Planned learning activities and teaching methods
Lectures, practical classes, consultations, independent work.
Assessment methods and criteria
Semester assessment: (maximum score of 60 points / marginal score of 36 points) 1. Surveys and problem solving – 20 points / 12 points; 2. Modular test work (2 MTW 10 points max. each) – 40 points / 24 points. The final assessment is conducted in the form of an exam with a maximum score of 40 points (marginal score of 24 points).
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Tetyana Viktorivna Kravets
Department of Economic Cybernetics
Faculty of Economics

Departments

The following departments are involved in teaching the above discipline

Department of Economic Cybernetics
Faculty of Economics