Statistical methods of software data processing

Course: Economic analysis and statistics

Structural unit: Faculty of Economics

Title
Statistical methods of software data processing
Code
3.1.1.
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
3
Learning outcomes
PLO 4. Use professional arguments to convey information, ideas, problems and ways to solve them to specialists and non-specialists in the field of economic activity PLO 5. Explain the models of socio-economic phenomena, guided by the fundamental principles and knowledge of the main directions of development of economic science. PLO 7. Understand the main features of the modern world and national economy, institutional structure, directions of social, economic and foreign economic policy of the state. PLO 10. Be able to analyze the processes of state and market regulation of socio-economic and labor relations. PLO 13. Be able to work both independently and in a team
Form of study
Prerequisites and co-requisites
Know the methods of analysis in the disciplines: "Statistics", "Programming". Be able to use software for processing large amounts of data and problem-oriented application packages.
Course content
The curriculum consists of two content modules: module - 1 "Automated Information Processing System", which discusses the principles of the application package Statistica: working interface, database management, creating a workbook and report files. Using the method of descriptive statistics: grouping and regrouping, generalization and comparison using averages, absolute and relative values, as well as methods of estimating and analyzing variation, differentiation, concentration and comparison of structures in time and space, module 2 - "Analytical statistics" methods of testing statistical hypotheses on: characteristics of the sample population, the correspondence of the empirical distribution to the theoretical, the significance of differences between means and particles in comparable populations, as well as variances, randomness of the relationship between traits; methods of analysis of development trends and seasonal fluctuations, index analysis.
Recommended or required reading and other learning resources/tools
Planned learning activities and teaching methods
The purpose of the discipline - is to master the methods of automation of statistical analysis. The educational task of the course is to study the main features of the application package Statistica in the analysis of socio - economic phenomena and processes.
Assessment methods and criteria
Forms of student assessment: - semester assessment of 75 points maximum / 45 points minimum: 1. Participation in laboratory classes (speeches, practical exercises) - 15 points / 9 points; 2. 2 tests (topics 1-5 and 6-9) - each 20 points / 12 points; 3. Performing independent work - 20 points / 12 points. - final assessment in the form of a test
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Department of Statistics, Information and Analytical Systems and Demography
Faculty of Economics

Departments

The following departments are involved in teaching the above discipline

Department of Statistics, Information and Analytical Systems and Demography
Faculty of Economics