Biostatistics

Programme Fact File

Study direction:
Life Sciences

Master’s study programme
accredited until 20.12.2029.

Degree conferred / qualification obtained:
Master's Degree of Natural Sciences in Biostatistics

Language: English

Credit points/ECTS: 80/120

Study location: Rīga

2 years

Places:
12 full fee

2700 EUR/year

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.

Download the booklet

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

Course code	Study course title	Īstenotājs	Kursa vadītājs	Credit points/ETCS
SL_111	Bayesian Statistics	Statistics Unit	Ziad Taib	2 / 3
SL_102	Biochemistry and Laboratory Diagnostics	Statistics Unit	Angelika Krūmiņa	2 / 3
SL_117	Categorical Data Analysis	Statistics Unit	Maksims Zolovs	2 / 3
SL_114	Causal Inference	Statistics Unit	Māris Munkevics	2 / 3
KPUMTK_015	Civil and Environmental Protection, First Aid	Department of Clinical Skills and Medical Technologies	Oļegs Sabeļņikovs	2 / 3
SL_107	Clinical Trials I	Statistics Unit	Ziad Taib	4 / 6
SL_115	Clinical Trials II	Statistics Unit	Ziad Taib	4 / 6
SL_110	Health Economics	Statistics Unit	Eva Petrošina	2 / 3
SL_101	Human Anatomy and Physiology	Statistics Unit	Angelika Krūmiņa	4 / 6
SL_103	Internal and Infectious Diseases	Statistics Unit	Angelika Krūmiņa	4 / 6
SL_112	Linear Models	Statistics Unit	Māris Munkevics	4 / 6
SL_105	Mathematical Methods	Statistics Unit	Jeļena Larina	4 / 6
SL_116	Nonparametric and Robust Methods	Statistics Unit	Jānis Valeinis	4 / 6
SL_104	Probability	Statistics Unit	Eva Petrošina	2 / 3
SL_113	Repeated Measures and Longitudinal Data	Statistics Unit	Ziad Taib	2 / 3
SL_109	Socio-Medical Approach in Quantitative Studies	Statistics Unit	Ieva Reine	2 / 3
SL_106	Statistical Inference	Statistics Unit	Jeļena Larina	4 / 6
SL_108	Statistical Programming and Data Management	Statistics Unit	Andrejs Ivanovs	4 / 6

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

Full list of requirements

What to study next?

Medicine (for example, public health)

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)

The study programme was developed with support from the project Reducing study programme fragmentation and promoting study internationalisation at Rīga Stradiņš University (project Nr. 8.2.1.0/18/A/014).