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
        
        
            2021/2022
        
    
            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
Departments
The following departments are involved in teaching the above discipline