Biometric statistics
Course: Economic analysis and statistics
Structural unit: Faculty of Economics
Title
Biometric statistics
Code
3.2.1.6
Module type
Вибіркова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
4 Semester
Number of ECTS credits allocated
5
Learning outcomes
PLO 1. Formulate, analyze and synthesize solutions to scientific and practical problems
PLO 4. Develop socio-economic projects and a system of integrated actions for their implementation, taking into account their objectives, expected socio-economic consequences, risks, legislative, resource and other constraints
PLO 9. Make effective decisions under uncertain conditions and requirements that require the application of new approaches, methods and tools of socio-economic research
PLO 15. To plan and carry out scientific and / or applied researches, to make the substantiated conclusions on results of researches, to present results, to argue the opinion
Form of study
Prerequisites and co-requisites
1. Successful mastering of the courses "Statistical Modeling and Forecasting", "Statistical Methods of Data Implementation".
2. Knowledge of the theory of statistics and econometrics.
3. Knowledge of the STATISTICA package.
Course content
Getting acquainted with the features of the methodology of biostatistics and mastering the basic techniques of statistical analysis and testing of statistical hypotheses that take place in the practice of clinical trials, interpretation of their results to establish patterns, as well as decision-making in terms of safety and effectiveness of treatment in clinical practice.
Recommended or required reading and other learning resources/tools
Planned learning activities and teaching methods
The purpose of the course is to develop students' theoretical knowledge and practical skills to quantify the relationships between phenomena and processes that take place in clinical practice 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 clinical data analysis.
Assessment methods and criteria
Forms of student assessment:
1. Preparation of the presentation - 10 points / 6 points.
2. Performing practical exercises 10 points / 6 points.
3. Test work №1 (topics 1-4); №2 (topics 5-8). - 10 points / 12 points.
4. Preparation and defense of the calculation and analytical project - 10 points / 6 points.
- final assessment in the form of an exam
Language of instruction
Ukrainian
Lecturers
This discipline is taught by the following teachers
Nataliia
Kovtun
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