Admission requirements
To start writing the thesis, the student should have obtained 60 EC from the Statistics and Data Science master programme.
To sit the final examination, the student should have obtained 90 EC from the programme.
Description
The topic of the thesis project should fit the perspective of the master Statistics and Data Science. The project can have a theoretical/methodological focus where new methods, models or algorithms are being studied or developed, or can be an applied project on a master level where non standard data analyses are carried out, or a combination of both. It may be carried out at the university or outside of the university (e.g., industry, governmental organizations). Each project should have a clearly defined research aim/question and should include the analysis of data (either real or simulated data). The thesis to be written is a scientific report about the models/algorithms studied and the data analysis.
All projects should have a supervisor from the master Statistics and Data Science (SDS supervisor). For external projects (i.e., projects not conducted at one of the Statistics/Data Science groups of the master Statistics and Data Science), a second supervisor is required from the location where the thesis project is conducted (the external supervisor). The SDS supervisor is responsible for the quality of the project and the thesis and will determine the final thesis grade together with the independent reader.
Carrying out the thesis project (30 EC)
The student will work on the thesis project for a duration of the final ±21 full time weeks of the Statistics and Data Science master (assuming 40 hours of study per week (30 EC) and no other obligations in the program).
In the thesis project the student:
Participates in activities in the working environment.
Participates in thesis project working groups.
Carries out the research of the thesis proposal and writes a thesis.
Presents the work of the thesis and defends the thesis.
Course Objectives
The thesis project has two general aims:
1. To gain experience as a working statistician/data scientist in a possible future working environment.
2. To carry out a research project and create a manuscript of students’ original work.
Specific aims regarding working as a statistician/data scientist in a possible future working environment:
To acquire new knowledge and skills relevant for the project.
To work in such a way that results are reproducible.
To evaluate their own work, to receive and process feedback and incorporate it in their own work, and to provide feedback to others.
To work with real data problems.
To interact and work together with peers, colleagues and superiors.
Specific aims regarding carrying out a research project and producing a manuscript of students’ own original work:
To obtain a deeper knowledge of statistical/data science methods in a specific area of application.
To apply knowledge, skills and understanding acquired during the research project in a critical, independent and systematic approach for modeling and evaluating complex phenomena.
To plan and execute tasks with appropriate methods within a given time frame.
To present clearly on the research, verbally as well as in writing.
Timetable
In MyTimetable, you can find all course and programme schedules, allowing you to create your personal timetable. Activities for which you have enrolled via MyStudyMap will automatically appear in your timetable.
Additionally, you can easily link MyTimetable to a calendar app on your phone, and schedule changes will be automatically updated in your calendar. You can also choose to receive email notifications about schedule changes. You can enable notifications in Settings after logging in.
Questions? Watch the video, read the instructions, or contact the ISSC helpdesk.
Note: Joint Degree students from Leiden/Delft need to combine information from both the Leiden and Delft MyTimetables to see a complete schedule. This video explains how to do it.
Mode of instruction
At the start of the semester in which students carry out the thesis project, they enroll in a thesis working group. The thesis working groups consist of approximately 15 students that share and discuss the quality of written work and discuss their work experiences. The meetings will be supervised by a staff member. The groups will meet monthly during the thesis project.
Assessment method
The student should have fulfilled the following requirements (Pass/Fail):
Participation in activities in the working environment,
Participation in at least four thesis working groups.
For the final grade, the student's accomplishments are weighted as follows:
50% of the grade is based on the written Master Thesis (including 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 defense of the Master Thesis.
The defense of the Master Thesis is to be understood as the Final Examination according the Course and Examination Regulations. The student should be physically present at the final presentation and defense of the master thesis, which cannot be conducted online.
Reading list
Brightspace E-learning Skills Platform: https://brightspace.universiteitleiden.nl/d2l/home/27150
Registration
More contact information will be provided on Brightspace.
Contact
The general e-mail address is thesis[at]stat.leidenuniv.nl
Remarks
Transitional arrangements
Transitional arrangements
The thesis project (in total 34 EC) replaces the separate internship (10 EC) and thesis (24 EC) projects that existed before September 2021. 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.
Software
Starting from the 2024/2025 academic year, the Faculty of Science will use the software distribution platform Academic Software. Through this platform, you can access the software needed for specific courses in your studies. For some software, your laptop must meet certain system requirements, which will be specified with the software. It is important to install the software before the start of the course. More information about the laptop requirements can be found on the student website.