Sampling Techniques
Course: Economic Cybernetics
Structural unit: Faculty of Economics
Title
Sampling Techniques
Code
ВБ 1.3
Module type
Вибіркова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
4 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 basics concepts of mathematics for economists (in particular, mathematical analysis and algebra), probability theory and mathematical statistics.
2. Have the elementary skills of solving applied problems using publicly available computer software.
Course content
The course structure has two modules:
Content module 1. "Simple and stratified selection", in which the main concepts are introduced, the main problems and tasks are formulated and formalized, and the basic mathematical toolkit for solving them is announced.
Content module 2. "Cluster and systematic selection", which analyzes various schemes of cluster and systematic selection and their relationship. Specific examples of the practical implementation of the methodology of conducting complex sample surveys are considered.
Recommended or required reading and other learning resources/tools
1. Черняк О. І. Техніка ви-біркових досліджень. – К.: КВІЦ, 2001.
2. Василик О.І., Яковенко Т.О. Лекції з теорії методів вибіркових обстежень. – К.: КПЦ «КУ», 2010. – 208 с.
3. Cochran W.G. Sampling Techniques. Wiley. 3-ed., 1977.
4. Lohr S.L. Sampling: De-sign and Analysis. Duxbury Press, 1999.
5. Wojna A.: Wykłady z podstaw statystyki. Część 1I. Elementy wnioskowania statystycznego oraz matematyczne metody pomiaru ryzyka. Koszalin, Politechnika Koszalińska 2015. 375 s.
: КВІЦ, 2001.
Planned learning activities and teaching methods
Lecture, seminar lesson, student’s self-study
Assessment methods and criteria
1. Self practical work in the computer class №1 – 2; LO1.1, LO1.2, LO2.1, LO2.2 : – 25 points.
№3 – 4; LO1.1, LO1.2, LO2.1, LO2.2, LO4.1: – 25 points.
2. Current assessment LO1.1, LO1.2, LO2.1, LO2.2, LO4.1, LO4.2: – 10 points.
3. Final test LO1.1, LO1.2, LO2.1, LO2.2, LO4.1, LO4.2. – 40 points.
Language of instruction
Ukrainian
Lecturers
This discipline is taught by the following teachers
Alexander
Andrejevich
Voina
Applied Statistics
Faculty of Computer Science and Cybernetics
Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
Applied Statistics
Faculty of Computer Science and Cybernetics