Probability Theory and Mathematical Statistics

Course: Economics (English/Ukrainian Taught)

Structural unit: Faculty of Economics

Title
Probability Theory and Mathematical Statistics
Code
ОK 12
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
6
Learning outcomes
PLO 5. To apply analytical and methodical tools for substantiating proposals and making managerial decisions by various economic agents (individuals, households, enterprises and government authorities). PLO 8. To apply appropriate economic and mathematical methods and models for solving economic problems. PLO 12. To apply the acquired theoretical knowledge to solve practical problems and interpret the obtained results in a meaningful way.
Form of study
Full-time form
Prerequisites and co-requisites
1. Know: the basic concepts of higher mathematics, 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. 2. Have the skills to calculate the boundaries of numerical sequences, calculating integrals.
Course content
The course structure has two modules: Content module 1. “Probability Theory” that discusses the basic concepts of probability theory, axioms of probability theory, discrete random variables, continuous random variables, limit theorems of probability theory. Content module 2. “Mathematical Statistics”, that discusses the main tasks of mathematical statistics, descriptive statistics, statistical estimation of unknown distribution parameters, statistical hypothesis testing, least squares method, linear regression, elements of analysis of variance.
Recommended or required reading and other learning resources/tools
1. Ross S.M. Introduction to Probability Models, 12th Edition, Academic Press, 2019. - 842p. 2. Ross S.M. Introduction to Probability and Statistics for Engineers and Scientists, 6th Edition, Academic Press, 2020. - 704p. 3. Roussas G. G. An Introduction to Probability and Statistical Inference, Second Edition, Academic Press, 2015. - 606p. 4. Leekley R. M. Applied Statistics for Business and Economics, CRC Press, 2010. – 476p. 5. Holmes A., Illowsky B., Dean S. Introductory Business Statistics, OpenStax, 2017. – 642p. 6. Bertsekas, D.P. and Tsitsiklis, J.N. Introduction to Probability, 2nd Edition, Athena Scientific, 2008. 7. Grinstead, C.M. Grinstead and Snell’s Introduction to Probability, University Press of Florida, 2009.
Planned learning activities and teaching methods
Lecture, practical lesson, student’s self-study
Assessment methods and criteria
1. Solving practical problems (LO 1.1-1.6) - 10 points / 6 points 2. Module test (2 Module tests, 20 points max. for each) (LO 1.1-1.6; 2.1-2.2; 4.1-4.2) – 40 points / 24 points; 3. The individual student’s self-study assignment (LO 1.1-1.6; 2.1-2.2; 4.1-4.2) – 25 points / 15 points; 4. Final test (РН 1.1-1.6; 2.1-2.2; 4.1-4.2) – 25 points / 15 points.
Language of instruction
English

Lecturers

This discipline is taught by the following teachers

Oksana Leonidivna Banna
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