TLÜ ÕIS

Multivariate Statistics

Course code

IFI7071.DT

old course code

IFI7071

Course title in Estonian

Mitmemõõtmeline statistika

Course title in English

Multivariate Statistics

ECTS credits

6.0

Assessment form

Examination

lecturer of 2025/2026 Autumn semester

Kaja Mädamürk (language of instruction:Estonian)

lecturer of 2025/2026 Spring semester

Not opened for teaching. Click the study programme link below to see the nominal division schedule.

Course aims

To create opportunities for acquiring additional knowledge in data analysis for those who, due to their specialisation or their interest and orientation, need the ability to interpret models describing multidimensional differences and relationships and to construct simpler multidimensional models themselves using appropriate software.

Brief description of the course

Overview of the most common multivariate statistical methods used in the social and educational sciences: multifactorial and multivariate analysis of variance, linear and logistic regression analysis, cluster analysis, factor analysis, multivariate scaling.
The theoretical basis of these statistical methods, the conditions under which they are applied and the interpretation of the results obtained when they are applied are outlined, based on specific data and the problems arising in the research. The course includes practical data analysis exercises.
To complete the course, students will be required to participate in seminar-type practical sessions, where they are expected to think and work actively. In addition, each student will be required to complete 7 practical group assignments consisting of practical data analysis tasks provided by the lecturer. A written test must be passed in order to obtain a mark.

Learning outcomes in the course

Upon completing the course the student:
- have experience in posing questions that require the formulation of data-driven and multidimensional statistical models;
- understand the nature of the multivariate statistical methods covered, know the conditions for their application and can interpret the results correctly;
- can select appropriate analysis methods (within the scope of the course) based on the type of data and the research questions posed;
- is capable of using relevant software, with the help of manuals, to construct simpler multivariate models (within the scope of the course).

Teacher

Kairi Osula

The course is a prerequisite

Interpretation of Research Results (PSP7038.LT)

Study programmes containing that course