# Programme structure

The study starts with the course **Introduction to Statistics** which presents the **basic ideas of statistics** without focusing too much on theory. It gives an **overview of the programme** and the methods that the student will learn at the other courses.

At the same time the student learns the **R statistical language** during the course **Computer Support of Statistics**, which helps him with learning the theory and solving practical problems. The language is used with most of the courses and is a **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 that did not listen to many mathematical courses during their first degree study (i.e. analysis, algebra and probability) 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 with mmore mathematical background) can instead of Mathematics for Statisticians choose the courses of **Bayesian Statistics** and **Probability**.

That is followed by the course **Introduction to Theoretical Statistics**, where the students learn 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 used in practice in the rest of the courses.

The course **Data Sources** informs the student about the availability and possibility of using important domestic and foreign sources of statistical data.

The compulsory courses address the **basic methods**, that are used in **all fields of statistics**. The elective courses, on the other hand, address the **specialty areas the student is interested in**. The combination of problems from different courses gives the student **a comprehensive picture of the statistical science**.

The study is concluded with **practical work** in the course **Statistical Consulting**, where the student can use the acquired knowledge and skills on real problems; and the **masters thesis** by which the student improves her knowledge in a particular field.

## 1st Year

Winter | Summer | Total | |
---|---|---|---|

Course | ECTS | ECTS | ECTS |

Introduction to Statistics | 5 | 5 | |

Computer Support of Statistics | 5 | 5 | |

Linear Models | 5 | 5 | |

Introduction to Theoretical Statistics | 5 | 5 | 10 |

Multivariate Analysis | 5 | 5 | |

Data Sources | 5 | 5 | |

Programme-bound elective course I | 5 | 5 | |

Programme-bound elective course II | 5 | 5 | |

Compulsory course depending on module | 5 | 5 | |

Elective course I | 5 | 5 | |

Elective course II | 5 | 5 | |

TOTAL |
60 |

## 2nd Year

Winter | Summer | Total | |
---|---|---|---|

Course | ECTS | ECTS | ECTS |

Computer Intensive Methods | 5 | 5 | |

Compulsory course depending on module | 5 | 5 | |

Elective course III | 5 | 5 | |

Elective course IV | 5 | 5 | |

Statistical Consulting | 10 | 10 | |

Thesis preparation | 30 | 30 | |

TOTAL |
60 |

## Programme-bound elective courses

1st year | ECTS |
---|---|

Mathematics for Statisticians | 10 |

Bayesian Statistics | 5 |

Probability | 5 |

## Compulsory courses depending on module

1st year | Module | ECTS |
---|---|---|

Experimental Design | Biostatistics, Technical Statistics | 5 |

Categorical and Measurement Models in Social Sciences | Social Science Statistics | 5 |

Economic statistics | Economic and Business Statistics | 5 |

Measure Theory | Mathematical Statistics | 5 |

Introduction to Machine Learning | Machine Learning | 5 |

Introduction to Official Statistics | Official Statistics | 5 |

2nd year | Module | ECTS |

Event History Analysis/Survival Analysis | Biostatistics | 5 |

Statistical Views of Data Collecting | Social Science Statistics | 5 |

Business Statistics | Economic and Business Statistics | 5 |

Statistics 2 | Mathematical Statistics | 5 |

Advanced Methods in Machine Learning | Machine Learning | 5 |

Statistical Process Control | Technical Statistics | 5 |

Methods and Tools of Official Statistics | Official Statistics | 5 |

## Elective courses

**Students of the modules Economic and Business Statistics or Official Statistics can and are encouraged to choose their elective courses from the following list of second level study courses of the Faculty of Economics:**

Econometrics 2 (Ekonometrija 2) |

Econometrics of Time Series and Panel Data (Ekonometrija časovnih vrst in panelnih podatkov) |

Demographics (Demografija) |

National Accounts and Input-Output Analysis (Nacionalno računovodstvo in input-output analiza) |

Research Methods in Tourism (Raziskovalne metode v turizmu) |

Satellite Accounts in Tourism (Satelitski računi v turizmu) |

**Students of the module Machine Learning can and are encouraged to choose their elective courses from the following list of second level study courses of the Faculty of Computer Science:**

Advanced Methods of Computer Vision (Napredne metode računalniškega vida) |

Natural Language Processing (Obdelava naravnega jezika) |

Introduction to Bioinformatics (Uvod v bioinformatiko) |

**With agreement of the module coordinator, the 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. **

Example of the study process for student of Economic and Business module: