Biostatistics (LV)
The study programme not only gives students the opportunity to acquire in-depth knowledge of methods for processing statistical data, but also enhances their understanding of the causes and development of the most common diseases, as well as epidemiological and clinical research.
Programme Fact File
Life Sciences
accredited until
Master's Degree of Natural Sciences in Biostatistics
12 full fee
Study environment, contents and methods
Study environment
The programme's students have access to well-equipped auditoriums and modern computer classrooms with the latest logistical resources, IT equipment, statistical software (R, SAS, IBM SPSS Statistics, STATA), audio and video equipment, interactive whiteboards, as well as a library with extensive research databases from around the world.
Course contents
The programme includes 4 main study course blocks:
- statistics courseson classical and innovative methods for processing statistical data are aimed at the use of methods for processing statistical data and analysing the obtained results in-depth;
- medicine courseson human anatomy, chemical processes, laboratory tests for diagnosis and the aetiology, diagnosis and treatment of the most common diseases, for students to understand and analyse the obtained data and be able to fully interpret the results;
- epidemiology courses focused on developing research skills, as well as on raising awareness of public health guidelines, research methodology and planning;
- clinical trial courseson organising research, drawing up of documentation, legislation, ethical aspects and key principles of data statistical processing.
- 1st Year
1st semester: introductory courses in medicine (Anatomy, Biochemistry, Internal and Infectious Diseases) and mathematics (Probability, Mathematical Methods and Statistical Inference) are planned at the beginning in order to adjust students’ knowledge. Later compulsory courses, such as Statistical Programming and Data Management, Socio-Medical Approach to Quantitative Studies and Clinical Trials will be introduced.
2nd semester: courses on classical data processing methods - Linear Models, Longitudinal Data Analysis, Non-parametric Methods, Categorical Data Analysis, Causal Inference, as well as the second cycle on Clinical Trials.
- 2nd Year
In the 2nd year of study, students will take study courses on classical methods (Survival Analysis, Multivariate Statistics) and innovative statistical methods (Machine Learning and Big Data Analysis), as well as Statistical Consulting, Epidemiology and Placement. Upon completion of studies, students will write and defend a Master’s thesis.
- Syllabus
Study methods
The study programme will be implemented by combining learning theoretical knowledge and developing skills, both with traditional lectures and interactive classes, as well as by studying independently. Modern learning and teaching methods, such as a simulation and project-based or problem-based learning approaches will be used.
The programme was developed in close cooperation with the University of Latvia, the University of Tartu, Uppsala University and the University of Gothenburg, involving the teaching staff from the aforementioned universities in the implementation of the courses. In addition, visiting lecturers from pharmaceutical companies from Latvia and abroad will be involved for integrating specialist knowledge.
Location
- 14 Baložu iela, Rīga
- Medical Education Technology Centre, 26A Anniņmuižas bulvāris
- Institute of Anatomy & Anthropology (Anatomical Theatre), 9 Kronvalda bulvāris
- RSU Main building, 16 Dzirciema iela
Career opportunities after graduation
Graduates from the study programme primarily work as biostatisticians in pharmaceutical companies and clinical research organisations (CRO), with planning data collection in clinical trials and observations, statistically processing the obtained data and analysing the results. Biostatisticians also work at universities, scientific institutes, laboratories and other research foundations that collect data and analyse results in health-related fields.
Admission requirements
- Main requirements Bachelor's degree or a second-level professional higher education in the following areas: mathematics and statistics, biology, programming, medicine, medical services, nursing, dentistry, pharmacy, public health;
- Certificate of English proficiency;
- Letter of motivation
What to study next?
- Medicine (for example, public health)
Read More
Transforming Data into Knowledge: RSU's New Biostatistics Programme Suits Medics, Mathematicians, and Biologists Alike (22 November 2022)
RSU To Have a New Biostatistics Master's Programme (7 April 2021)
Head of Programme
Working hours:
Pēc iepriekšēja pieraksta
rsu [pts] lv
