Mathematical demography and modeling of random processes. Module 1. Mathematical demography
Course: System Analysis
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Mathematical demography and modeling of random processes. Module 1. Mathematical demography
        
    
            Code
        
        
            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
        
        
            6 Semester
        
    
            Number of ECTS credits allocated
        
        
            2
        
    
            Learning outcomes
        
        
            Know and understand the basic models of births, growth, movement and mortality.
Be able to calculate or evaluate 40 basic numerical indicators of demographic models; calculate forecast values and their accuracy.
Demonstrate the ability to self-study and continue professional development.
Be able to organize their own activities and get results within a limited time.
Demonstrate skills of interaction with other people, ability to work in teams.
        
    
            Form of study
        
        
            Full-time form
        
    
            Prerequisites and co-requisites
        
        
            Know: basics of discrete mathematics, probability theory and mathematical statistics
Be able to: formalize the conditions of problems and make a solution plan
Have basic skills: solve typical problems in probability theory,
mathematical statistics and discrete mathematics.
        
    
            Course content
        
        
            The discipline "Mathematical Demography" is an integral part of the cycle of professional training of specialists of educational and qualification level "Bachelor"; it includes the study of models of births, growth, movement, mortality. It is also mandatory to master the basic formulas and methods of their application. Particular attention is paid to the application of stochastic and deterministic models of mathematics in the study of models of births, growth, movement and mortality. Students are introduced to the basic definitions, given the interpretation of formulas. In addition to the classic sections, the issues of population growth on the Earth, socio-economic aspects of demography and life insurance are considered. Discipline is the discipline of choice.  Taught in the 6th semester, 75 hours. (2 ECTS credits), of which lectures - 34 hours, consultations - 1 hour, independent work - 40 hours. There are 2 content parts and an exam.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            Planned learning activities and teaching methods
        
        
            Lecture, individual work
        
    
            Assessment methods and criteria
        
        
            Current assessment, control work, exams
        
    
            Language of instruction
        
        
            Ukrainian
        
    Lecturers
This discipline is taught by the following teachers
                    Mykhailo
                    Mykhailovich
                    Sharapov
                
                
                    Applied Statistics 
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
                    Mykhailo
                    Mykhailovich
                    Sharapov
                
                
                    Applied Statistics 
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
                        Applied Statistics
                    
                    
                        Faculty of Computer Science and Cybernetics
                    
                
                        Applied Statistics
                    
                    
                        Faculty of Computer Science and Cybernetics