Year 1
| Vak | EC | Semester 1 | Semester 2 |
|---|---|---|---|
|
Mandatory: |
|||
| Mathematics for statisticians | 3 | ||
| Statistics and probability | 9 | ||
| Statistical computing with R | 6 | ||
| Introduction to Data Science | 3 | ||
| Linear & generalized linear models and linear algebra | 9 | ||
| Bayesian Statistics | 6 | ||
| Databases | 6 | ||
| Mixed and longitudinal modeling | 6 | ||
| Multivariate analysis and multidimensional data analysis | 6 | ||
|
Preapproved Electives: |
|||
| Study designs in the Life and Behavioral Sciences | 6 | ||
| Survey Methodology | 6 | ||
| Survival analysis | 6 | ||
Year 2
| Vak | EC | Semester 1 | Semester 2 |
|---|---|---|---|
|
Mandatory: |
|||
| Advanced Statistical Computing | 3 | ||
| Statistical Consulting (Statistical Science) | 5 | ||
| Statistical learning | 6 | ||
| Internship | 10 | ||
| Master Thesis | 24 | ||
|
Preapproved Electives: |
|||
| Psychometrics and SEM | 6 | ||
| Advances in Data Mining | 6 | ||
| Introduction to Deep Learning | 6 | ||
| High-dimensional data analysis | 6 | ||
| Statistical genetics | 6 | ||
| EMOS Core Module | 12 | ||