Statistical data analysis
Course: Economic analysis and statistics
Structural unit: Faculty of Economics
Title
Statistical data analysis
Code
2.1.8.
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
7 Semester
Number of ECTS credits allocated
5
Learning outcomes
PLO 3. Use analytical and methodological tools to understand the logic of economic decision-making by various economic agents (individuals, households, enterprises and public authorities)
PLO 6. Apply appropriate economic-mathematical and statistical methods and models to solve economic problems
PLO 10. Be able to analyze the processes of state and market regulation of socio-economic and labor relations
PLO 11. Apply the acquired theoretical knowledge to solve practical problems and interpret the results
PLO 13. Be able to work both independently and in a team
Form of study
Prerequisites and co-requisites
The basis of the study of this discipline is the successful mastering of courses related to statistical methods of data analysis.
1. Know the methods of statistics and econometrics; application packages and the ability to work in them; SQL.
2. Have programming skills in SQL.
In turn, knowledge of this discipline contributes to the successful implementation of the analytical part of the dissertation, which will be the evidence of the scientific work, as well as writing scientific articles.
Course content
Getting acquainted with statistical programming and mastering the basic techniques of statistical analysis using SAS software, developing the ability to visualize and interpret results in order to identify trends and patterns of development and decision-making.
Recommended or required reading and other learning resources/tools
Planned learning activities and teaching methods
The purpose of the discipline is to continue the formation of students' theoretical knowledge and practical skills in statistical programming to analyze the processes taking place in the economy and social sphere on the basis of the original data set to ensure the reliability of conclusions and recommendations. The educational task of the course is to develop practical skills of analysis of complex databases using SAS.
Assessment methods and criteria
Forms of student assessment: (max. Points 60 / minimum points 36):
1. Performing practical exercises 20 points / 12 points.
2. Test modular work - 20 points / 12 points.
3. Preparation and defense of an individual program project - 20 points / 12 points.
- final assessment in the form of an exam
Language of instruction
Ukrainian
Lecturers
This discipline is taught by the following teachers
Departments
The following departments are involved in teaching the above discipline