Probability theory and mathematical statistics
Course: Educational program Accounting and Taxation
Structural unit: Faculty of Economics
            Title
        
        
            Probability theory and mathematical statistics
        
    
            Code
        
        
            OK 1.12
        
    
            Module type 
        
        
            Обов’язкова дисципліна для ОП
        
    
            Educational cycle
        
        
            First
        
    
            Year of study when the component is delivered
        
        
            2021/2022
        
    
            Semester/trimester when the component is delivered
        
        
            2 Semester
        
    
            Number of ECTS credits allocated
        
        
            5
        
    
            Learning outcomes
        
        
            PL14. Be able to apply economic and mathematical methods in the chosen profession. PL15. Possess general scientific and special methods of research of socio-economic phenomena and economic processes at the enterprise.
        
    
            Form of study
        
        
            Prerequisites and co-requisites
        
        
            1. Know: the basic concepts of higher mathematics, including methods for calculating the boundaries of numerical sequences and functions, the concept of numerical series, methods for studying the convergence of numerical series, methods for calculating integrals, set theory.
2. Have the skills to calculate the boundaries of numerical sequences, calculating integrals.
        
    
            Course content
        
        
            The curriculum consists of two content modules:
Content module 1. "Probability Theory", which discusses the basic concepts of probability theory, axioms of probability theory, discrete random variables, continuous random variables, limit theorems of probability theory.
Content module 2. "Mathematical Statistics", which discusses the main problems of mathematical statistics, descriptive statistics, statistical evaluation of unknown parameters of distributions, testing statistical hypotheses, least squares method, linear regression, elements of analysis of variance and time series analysis.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            Planned learning activities and teaching methods
        
        
            Lectures, practical classes, consultations, independent work
        
    
            Assessment methods and criteria
        
        
            Semester assessment:
1. Modular test (2 MCR, 20 points max. Each) (PH 1.1-1.5; 2.1-2.2; 4.1-4.2) - 40 points / 24 points;
2. Independent work - calculated individual task (RN 1.1-1.6; 2.1-2.2; 4.1-4.2) - 20 points / 12 points.
Final evaluation:
A student is not allowed to take the exam if he / she received less than 36 points during the semester.
        
    
            Language of instruction
        
        
            Ukrainiane
        
    Lecturers
This discipline is taught by the following teachers
                    Yurii
                    Petrovych
                    Tadeyev
                
                
                    Department of Economic Cybernetics 
Faculty of Economics
            Faculty of Economics
Departments
The following departments are involved in teaching the above discipline
                        Department of Economic Cybernetics
                    
                    
                        Faculty of Economics