o To start the preparations of the thesis (the mandatory lectures/working groups and the writing of the proposal) the student should have 42EC of the programme.
o To carry out the proposal, the student should have obtained 60 EC from the programme.
o To sit the final examination, the student should have obtained 96 EC from the programme.
The thesis project is a project of 34 EC consisting of
o Preparation of the thesis project (4EC)
o Carry out the thesis project (30EC)
The thesis project may be an academic project on a methodological topic, or an applied project where a non standard data analysis is carried out, or a combination of both (start with a more applied internship, related topic for academic thesis).
It may be carried out outside of university (industry, governmental organisations, etc.) or at the university. A project outside of university can be carried out under a local supervisor, but an examiner of the Statistics and Data Science staff (i.e., a person who holds a PhD and is connected to one of the four participating statistical groups) is involved as supervisor on a regular basis ,and is responsible for the quality of the project and the thesis and will assess the grade (together with the independent second reader).
Preparation of the thesis project (4 EC)
The student follows mandatory lectures and working groups on academic integrity and responsible research, and writes the proposal for the thesis project.
Carrying out the thesis project (30 EC)
The student will work on the thesis project for a duration of the remaining ±22 full time weeks (when taking into account 40 hours of study per week (30 EC), and assuming that there are no other obligations in the programme).
In the thesis project the student:
o participates in activities in the working environment
o participates in thesis project working groups
o writes a mid-way report
o carries out the research of the thesis proposal and writes a thesis.
o presents the work of the thesis and defends the thesis.
The thesis project (34 EC) replaces the former separate internship (10 EC) and thesis (24 EC). Students who started before September 2021 are still allowed to plan their thesis and internship as separate projects, provided they did not interrupt their registration.
The thesis project has two general aims:
o To gain experience as a working statistician/data scientist in a possible future working environment
o To carry out a research project and produce a manuscript of students’ original work.
The specific learning aims are listed below:
a. Preparation of the thesis project.
o is able to reflect on research integrity dilemmas within methodological research and when applying statistics and data science.
o is aware of the three major violations to good scientific conduct: Fabrication, Falsification, Plagiarism, and knows how he can avoid or detect them.
o is aware of the Leiden University policies on academic integrity, and knows that he is obliged to follow these policies.
o has read and understood at least one of the ethical guidelines of the major professional bodies in statistics and mathematics, such as those of the Royal Statistical Society, the American Statistical Association, or the European Mathematical Society.
o understands the importance of working in a transparent reproducible way.
o knows the tools to work in a transparent reproducible way (working with scripts, github, version control).
o is aware of privacy regulations (General Data Protection Regulation).
o is able to develop a research plan and write a proposal for his thesis, which includes a description of the background, formulation of research aims and objectives, and a work plan.
b. Thesis project
Aims regarding gaining experience as a working statistician in a possible future working environment
The student is able to:
o acquire new knowledge and skills relevant for the project.
o work in such a way that results are reproducible.
o judge own work, is open for criticism and is able to incorporate feedback.
o work with real data problems.
o Is able to interact and work together with peers, collegues and superiors.
o provide feedback to others.
o participate pro-actively in the day-to-day interactions within the working environment.
Aims regarding carrying out a research project and produce a manuscript of students’ original work.
o obtain a deeper knowledge of statistical/data science methods in a specific chosen area of application’.
o apply knowledge, skills and understanding acquired during the study in a critical, independent, systematic approach to model and evaluate complex phenomena.
o plan and execute tasks with appropriate methods within a given time frame.
o present clearly on the research, verbally as well as in writing.
o is able to communicate the results to non-statisticians/data scientists.
Mode of instruction
When preparing for the thesis project the student has to follow mandatory lectures and working groups.
When the students starts writing the thesis proposal he/she enrolls in a thesis working group. The thesis working groups consist of a group of students (approximately 10) that share their written work (both proposals and thesis reports) and orally discuss the quality of the work and their work experiences. The working groups are dynamic, in the sense that there is a mixture of students who just started the thesis project and students who are already working on it for a longer time period. The meeting will be supervised by a staff member. The groups will meet monthly.
The student should have fulfilled the following requirements (for Pass/ Fail):
Active participation in mandatory working groups and lectures
The writing of the thesis proposal
Participate in activities in the working environment
Participate in the thesis working groups
The writing of a midway report
For the final grade, the student's accomplishments are weighted as follows:
50% of the grade is based on the written Master Thesis (including the appendices)
30% of the grade is based on the general working attitude during the thesis project
10% of the grade is based on the final presentation of the Master Thesis.
10% of the grade is based on the defence of the Master Thesis
The defence of the Master Thesis is to be understood as the Final Examination according the Course and Examination Regulations.