Mathematical Statistics for Economists

Course: Economic Cybernetics

Structural unit: Faculty of Economics

Title
Mathematical Statistics for Economists
Code
ОК 28
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
3 Semester
Number of ECTS credits allocated
5
Learning outcomes
PLO8. Apply appropriate economic-mathematical methods and models to solve economic problems. PLO12. Apply the acquired theoretical knowledge to solve practical problems and meaningfully interpret the results. PLO13. Identify sources and understand the methodology for determining and methods of obtaining socio-economic data, collect and analyze the necessary information, calculate economic and social indicators. PLO21. Be able to think abstractly, apply analysis and synthesis to identify key characteristics of economic systems at different levels, as well as the behavior of their subjects.
Form of study
Full-time form
Prerequisites and co-requisites
1. Know: the basic concepts of Mathematics and Probability Theory, including methods for calculating the boundaries of numerical sequences and functions, the concept of numerical series, methods for studying the convergence of numerical series, methods for calculating integrals, set theory, distributions of random variables, limit theorems of Probability Theory. 2. Have the skills to calculate the boundaries of numerical sequences, calculating integrals and probabilities of random events.
Course content
The course structure has two modules: Content module 1. "Basic concepts of mathematical statistics, estimation of unknown parameters", that discusses the main problems of mathematical statistics, descriptive statistics, sampling and its characteristics, statistical estimation of unknown parameters of distributions. Content module 2. "Statistical hypothesis testing, elements of regression, variance, discriminant analysis, time series analysis", which includes the main methods of statistical hypothesis testing, sequential analysis, elements of correlation and regression analyses, linear regression, elements of variance analysis, elements of discriminant analysis , basic methods of time series analysis.
Recommended or required reading and other learning resources/tools
1. Черняк О.І., Кравець Т.В., Ляшенко О.І. Буяк Л.М., Банна О.Л., Башуцька О.С. Теорія ймовірностей та математична статистика. Практикум: навчальний посібник. – Т.: ТНЕУ, 2019. – 251 с. 2. 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. –71 с. 3. Васильків І.М. Основи теорії ймовірностей і математичної статистики: навчальний посібник. –Львів: ЛНУ імені Івана Франка, 2020. – 184 с. 4. Алілуйко А. М., Дзюбановська Н. В., Єрьоменко В. О., Мартинюк О. М., Шинкарик М. І. Практикум з теорії імовірностей та математичної статистики. Навчальний посібник для студентів економічних спеціальностей. – Тернопіль: Підручники і посібники, 2018. – 352 с. 5. Holmes A., Illowsky B., Dean S. Introductory Business Statistics, OpenStax, 2017. – 642p.
Planned learning activities and teaching methods
Lecture, practical lesson, student’s self-study
Assessment methods and criteria
1. Module test (2 Module tests, 20 points max. for each) (LO 1.1-1.4; 2.1-2.2; 4.1) - 40 points / 24 points; 2. Self-study assignment, which includes the search for economic information in the form of time series, analysis of this information, construction of a linear regression model based on the obtained data, estimation of regression parameters, economic conclusions (LO 1.1, 1.4; 2.1-2.2; 4.1) - 20 points / 12 points.
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Viktor Vasylovych Shpyrko
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