# Trajectories

The Master of Statistical Data Analysis is an intensive program which strengthens hand-on data analysis experience through project assignments, many of which involve group work. For students with a full time or part time job, spreading the program over different years will therefore required. For students with a full time job, we recommend spreading the program over 3 to 4 years. In planning your curriculum, please note that the course Principles of Statistical Data Analysis is a prerequisite for all other courses and thus must be taken in the first year. The course Analysis of Continuous Data (Stat. Science track) or Statistical Modelling (Comp. Stat. track) is a prerequisite for many other courses, so that it is recommended to take this course in the first year. Please try to take compulsory courses as much as possible prior to elective courses; in particular, it is not allowed to take the course Statistical Inference (Stat. Science track) or Big Data Science (Comp. Stat. track) in the second (or later) years when elective courses are selected in the second semester of the first year. Upon registration, you will be asked to submit your selection of courses for the current academic years (not the subsequent years) via the electronic Oasis system. After submitting your proposed course trajectory, we will notify you in due course regarding the appropriateness of the proposed track. Below, we give you some guidance regarding spreading the program over 2, 3 or 4 years.

## Major Statistical Science

If you plan to spread the program over 2 years, then the following trajectory is recommended:

year |
1st semester |
2nd semester |

year 1 | Principles of Statistical Data Analysis | Statistical Inference |

Analysis of Continuous Data | Experimental Design (optional) | |

Statistical Computing | Analysis of High Dimensional Data (optional) | |

year 2 | Categorical Data Analysis | max 2 optional courses |

max 2 optional courses | Master dissertation |

If you plan to spread the program over 3 years, then the following trajectory is recommended:

** **

year |
1st semester |
2nd semester |

year 1 | Principles of Statistical Data Analysis | Statistical Inference |

Analysis of Continuous Data OR Statistical Computing | Experimental Design (optional) OR Analysis of High Dimensional Data (optional) | |

year 2 | Categorical Data Analysis | max 2 optional courses |

Analysis of Continuous Data OR Statistical Computing | ||

year 3 | max1 optional course | max 1 optional course AND Master dissertation |

If you plan to spread the program over 4 years, then the following trajectory is recommended:

year |
1st semester |
2nd semester |

year 1 | Principles of Statistical Data Analysis | Statistical Inference |

Analysis of Continuous Data OR Statistical Computing | ||

year 2 | Categorical Data Analysis | 1 optional course |

Analysis of Continuous Data OR Statistical Computing | ||

year 3 | max 2 optional courses | max 2 optional courses |

year 4 | Master dissertation |

## Major Computational Statistics

If you plan to spread the program over 2 years, then the following trajectory is recommended:

year |
1st semester |
2nd semester |

year 1 | Principles of Statistical Data Analysis | Big Data Science |

Statistical Modelling | max 2 optional courses | |

Statistical computing | ||

year 2 | Programming and Algorithms | max 1 optional course |

Databases | Master Dissertation |

If you plan to spread the program over 3 years, then the following trajectory is recommended:

year |
1st semester |
2nd semester |

year 1 | Principles of Statistical Data Analysis | 1 optional course |

Statistical Modelling OR Statistical computing | ||

year 2 | Statistical Modelling OR Statistical computing | Big Data Science |

Programming and Algorithms | ||

year 3 | Databases | 1 optional course |

Master Dissertation |

If you plan to spread the program over 4 years, then the following trajectory is recommended:

year |
1st semester |
2nd semester |

year 1 | Principles of Statistical Data Analysis | 1 optional course |

Statistical Modelling OR Statistical computing | ||

year 2 | Statistical Modelling OR Statistical computing | Big Data Science |

Programming and Algorithms | ||

year 3 | Databases | 1 optional course |

year 4 | Master Dissertation |