List of programme's course units, number of exams (i.e. how many times the exam was taken in a year) and average marks
The data refer to last year. A course unit may include modules, subgroups, integrated exams. Proficiency tests are not included in the list.
| Course unit | Number of times exam was taken | Average mark |
|---|---|---|
| LATENT VARIABLE MODELS | 67 | 26 |
| BAYESIAN INFERENCE | 63 | 27 |
| TIME-TO-EVENT DATA ANALYSIS | 2 | 25 |
| POPULATION AND CLIMATE CHANGE | 19 | 27 |
| ADVANCED SURVIVAL ANALYSIS | 1 | 30 |
| STOCHASTIC PROCESSES | 70 | 27 |
| DATABASES | 20 | 24 |
| STATISTICAL MODELS AND APPLICATIONS | 69 | 24 |
| METHODS AND TOOLS FOR OFFICIAL STATISTICS: SOCIO-ECONOMIC STATISTICS | 9 | 27 |
| DIFFERENTIAL EQUATIONS | 31 | 27 |
| SUPERVISED STATISTICAL LEARNING | 61 | 27 |
| MODERN STATISTICS AND BIG DATA ANALYTICS | 60 | 28 |
| BIODEMOGRAPHY | 19 | 29 |
| STATISTICAL MODELS FOR (FUZZY) SET-VALUED DATA | 3 | 29 |
| EXPERIMENTAL PSYCHOLOGY | 5 | 30 |
| COMPUTATIONAL HUMAN GENOMICS | 5 | 28 |
| BIG DATA (PRIVACY) | 2 | 27 |
| STATISTICAL SOFTWARE | 1 | 30 |
| METHODS AND TOOLS FOR HEALTH STATISTICS | 14 | 27 |
| ADVANCED SURVIVAL ANALYSIS | 20 | 28 |
| SOCIAL DEMOGRAPHY | 10 | 29 |
| ECONOMETRICS | 5 | 24 |
| DIFFERENTIAL CALCULUS | 12 | 26 |
| MACHINE LEARNING SYSTEMS FOR DATA SCIENCE | 2 | 29 |
| BAYESIAN INFERENCE | 85 | 28 |
| MULTIVARIATE STATISTICS | 17 | 25 |
| MEASURE THEORY | 8 | 29 |
| SOCIOGENOMICS | 25 | 29 |
| DATA SCIENCE APPLICATIONS | 4 | 29 |
| METHODS AND TOOLS FOR OFFICIAL STATISTICS: POPULATION AND HEALTH STATISTICS | 8 | 28 |
| ADVANCED TIME SERIES | 71 | 28 |
| ANALYSIS OF CATEGORICAL DATA | 19 | 25 |
| ADVANCED PROBABILITY | 60 | 27 |
| FUNDAMENTAL CONCEPTS OF STATISTICS | 102 | 28 |
| HUMAN GENETICS | 25 | 29 |
| DISCRETE MATHEMATICS | 3 | 27 |
| OPTIMAL DESIGN OF EXPERIMENTS | 6 | 28 |
