Software environment R
Course: Economic analysis and statistics
Structural unit: Faculty of Economics
            Title
        
        
            Software environment R
        
    
            Code
        
        
            1.7
        
    
            Module type 
        
        
            Обов’язкова дисципліна для ОП
        
    
            Educational cycle
        
        
            Second
        
    
            Year of study when the component is delivered
        
        
            2023/2024
        
    
            Semester/trimester when the component is delivered
        
        
            1 Semester
        
    
            Number of ECTS credits allocated
        
        
            5
        
    
            Learning outcomes
        
        
            PLO 3. To communicate freely on professional and scientific issues in the state and foreign languages orally and in writing
PLO 8. Collect, process and analyze statistical data, scientific and analytical materials needed to solve complex economic problems.
PLO10. Apply modern information technologies and specialized software in socio-economic research and management of socio-economic systems.
PLO 17. Use modern educational and research technologies in the field of economics.
        
    
            Form of study
        
        
            Distance form
        
    
            Prerequisites and co-requisites
        
        
            1. Know: the theory of methods of statistical analysis (disciplines: Statistics, Statistics for economists).
2. Possess: programming methods (disciplines: Fundamentals of programming, programming, Python and others).
        
    
            Course content
        
        
            The curriculum consists of one module: Software environment R. How to program in R, how to use programming language R for effective analysis of economic data, installation and configuration of software required for statistical programming environment, description of general concepts of programming languages during their implementation at a high level of statistical language, practical issues of statistical calculations, including programming in R, reading data in R.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            1. S. van Buuren. Flexible Imputation of Missing Data. Chapman & Hall/CRC Interdisciplinary Statistics. CRC Press LLC, 2018. ISBN 9781138588318
2. Dan E. Kelley. Oceanographic Analysis with R. Springer-Verlag, New York, October 2018. ISBN 978-1-4939-8842-6
3. Sarah Stowell. Using R for Statistics. Apress, 2014. ISBN 978-1484201404
4. Vikram Dayal. An Introduction to R for Quantitative Economics: Graphing, Simulating and Computing. Springer, 2015. ISBN 978-81-322-2340-5
5. C. Sun. Empirical Research in Economics: Growing up with R. Pine Square, Starkville, Mississippi, USA, 1st edition, 2015
        
    
            Planned learning activities and teaching methods
        
        
            The purpose of the discipline - Formation of students' necessary theoretical knowledge and practical skills for the effective use of programming language R with the use of special libraries of analysis and visualization of data for further use in professional activities.
        
    
            Assessment methods and criteria
        
        
            Forms of student assessment: (max. Points 60 / min. Points 36)
1. Performance of practical and laboratory works  - 48 points / 30 points;
2. Independent work - estimated individual task  - 12 points / 6 points;
- final assessment in the form of an exam
        
    
            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
            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