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