Program Overview

Master's Programme in Applied Statistics

The Master's programme in Applied Statistics is designed to provide students with a comprehensive understanding of statistical concepts and methods. The programme starts with the course Introduction to Statistics, which presents the basic ideas of statistics without focusing too much on theory. This course gives an overview of the programme and the methods that the student will learn in other courses.

Programme Structure

The programme structure is designed to provide students with a strong foundation in statistics. The study begins with the course Introduction to Statistics, followed by Computer Support of Statistics, where students learn the R statistical language. This language is used in most courses and is an indispensable tool for understanding theoretical concepts and doing statistical analyzes.

The mathematical support for the study of statistics comes in with the programme-bound elective courses. Students who did not take many mathematical courses during their first degree study attend the course Mathematics for Statisticians, which assures all students have the necessary mathematical knowledge and presents to them the mathematical tools needed for understanding statistics. Other students can choose the courses Bayesian Statistics and Probability.

The course Introduction to Theoretical Statistics provides students with the theoretical backgrounds of statistics and how to formulate statistical problems and solve them. Together with the course Mathematics for Statisticians, they build a strong theoretical foundation, which will be used in practice in the rest of the courses.

The course Data Sources informs students about the availability and possibility of using important domestic and foreign sources of statistical data. The compulsory courses address the basic methods used in all fields of statistics, while the elective courses address specialty areas the student is interested in. The combination of problems from different courses gives students a comprehensive picture of statistical science.

The study is concluded with practical work in the course Statistical Consulting, where students can use the acquired knowledge and skills on real problems, and the master's thesis, by which students improve their knowledge in a particular field.

1st Year

The first year of the programme includes the following courses:

• Introduction to Statistics (5 ECTS)
• Computer Support of Statistics (5 ECTS)
• Linear Models (5 ECTS)
• Introduction to Theoretical Statistics (10 ECTS)
• Multivariate Analysis (5 ECTS)
• Data Sources (5 ECTS)
• Programme-bound elective course I (5 ECTS)
• Programme-bound elective course II (5 ECTS)
• Compulsory course depending on module (5 ECTS)
• Elective course I (5 ECTS)
• Elective course II (5 ECTS) Total ECTS: 60

2nd Year

The second year of the programme includes the following courses:

• Computer Intensive Methods (5 ECTS)
• Compulsory course depending on module (5 ECTS)
• Elective course III (5 ECTS)
• Elective course IV (5 ECTS)
• Statistical Consulting (10 ECTS)
• Thesis preparation (30 ECTS) Total ECTS: 60

Programme-bound Elective Courses

The programme-bound elective courses include:

1. Mathematics for Statisticians (10 ECTS)
2. Bayesian Statistics (5 ECTS)
3. Probability (5 ECTS)

Compulsory Courses Depending on Module

The compulsory courses depending on the module include: 1st year:

• Experimental Design (Biostatistics, Technical Statistics) (5 ECTS)
• Categorical and Measurement Models in Social Sciences (Social Science Statistics) (5 ECTS)
• Economic statistics (Economic and Business Statistics) (5 ECTS)
• Measure Theory (Mathematical Statistics) (5 ECTS)
• Introduction to Machine Learning (Machine Learning) (5 ECTS)
• Introduction to Official Statistics (Official Statistics) (5 ECTS) 2nd year:
• Event History Analysis/Survival Analysis (Biostatistics) (5 ECTS)
• Statistical Views of Data Collecting (Social Science Statistics) (5 ECTS)
• Business Statistics (Economic and Business Statistics) (5 ECTS)
• Statistics 2 (Mathematical Statistics) (5 ECTS)
• Advanced Methods in Machine Learning (Machine Learning) (5 ECTS)
• Statistical Process Control (Technical Statistics) (5 ECTS)
• Methods and Tools of Official Statistics (Official Statistics) (5 ECTS)

Elective Courses

The elective courses include:

• Network Analysis (5 ECTS)
• Survey Research (5 ECTS)
• Time Series (5 ECTS)
• Optimization (5 ECTS)
• Design and Analysis of Clinical and Epidemiological Research (5 ECTS)
• Advanced R (5 ECTS)
• Generalized Linear Models (5 ECTS)
• Modelling Temporal and Spatial Processes (5 ECTS)
• Statistical Quality Control (5 ECTS)
• Statistical Support for Health Care Quality and Management (5 ECTS)
• Statistical Methods for High-dimensional Data (5 ECTS)
• Statistical Modeling in Biomedicine (5 ECTS)
• Scientific and Technical Communication (5 ECTS)

Students of the modules Economic and Business Statistics or Official Statistics can choose their elective courses from the list of second-level study courses of the Faculty of Economics, which includes:

• Econometrics 2
• Econometrics of Time Series and Panel Data
• Demographics
• National Accounts and Input-Output Analysis
• Research Methods in Tourism
• Satellite Accounts in Tourism

Students of the module Machine Learning can choose their elective courses from the list of second-level study courses of the Faculty of Computer Science, which includes:

• Advanced Methods of Computer Vision
• Natural Language Processing
• Introduction to Bioinformatics

With the agreement of the module coordinator, students can earn 10 ECTS by attending courses from other second-level study programmes of the University of Ljubljana or comparable programmes of foreign universities.