The workload for this Master's programme is 120 EC, equally distributed over two academic years of two semesters each. All students of a given cohort enter the programme together at the beginning of the academic year, following as a group each of the eight courses of the first year. We expect you to work for 40 hours per week, including preparing for classes and working on assignments. There are on average about twelve contact hours (attending lectures and lab meetings) per week.
All courses run in parallel for the full length of a semester and have been specifically developed for the MSBBSS programme. Courses and other curriculum components build upon each other regarding prerequisites and content, i.e., the content of the course is aligned to what is already being taught in previous courses.
In the first year, the programme provides a broad and solid basis with ingredients essential for any job in the field of methodology and statistics within and outside academia. Throughout the first year four components reappear:
- methodological/statistical theory and developing new statistical techniques/methods;
- putting the theory to practice (e.g., designing an experiment or writing an R programme);
- applications of existing software (R and Mplus) to empirical data from the behavioural, biomedical, and social sciences;
- critical reflections on what is being done. Students do not only learn the technical background of each method, but they also learn to understand, compare, and criticise the different approaches in relation to each other and discuss when to apply which methods.
Our Master's programme has a strong preference for Open Science, including RRP (responsible research practices), the DORA declaration, FAIR principles, and VSNU guidelines on research integrity. Such topics are an integral part of the entire curriculum. In many courses these topics are actively discussed, and skills for reproducible coding are being taught and put to practice for the thesis.
The challenge in the first couple of weeks is to prepare for the intensive programme. Especially in the first couple of weeks many you have to get used to the dense programme and the many deadlines. Also, often international students have to get acquainted to the Dutch educational and grading system.
Based on the broad knowledge and skills basis acquired in the first year, you now explore a contemporary research topic into depth.
There are plenty of options to design an individual programme in the field of your own interest as part of the electives. This can for example be a series of courses on data science, survey research, math/calculus, or biomedical research. There is also the option to do a traineeship. You can also choose to follow one of our predefined tracks.
The Master’s thesis is executed under the supervision of staff members of one of the departments executing MSBBSS or under the supervision of a staff member of one of the non- academic organisations associated with MSBBSS (e.g., Statistics Netherlands, Cito, TNO).
While writing your thesis, you are coached with respect to scientific writing and presenting, working in a group, and scientific integrity in conducting, archiving, and reporting research. Additionally, you are trained in methodological and statistical consultation and obtain experience by participating in a consultation shop. They advise you with respect to the methods and statistics you use in your thesis.
The emphasis throughout the programme is on active learning. That is, there are relatively few traditional, stand-and-deliver lectures (“teaching by telling” approach focused on delivering knowledge and information). Rather, in all courses, active, stimulating learning methods are used that engage you with questions or group activities, as opposed to passively taking in the information. You are required to actively reflect on the course literature before the course meetings and contribute to group discussions during the meetings.
The courses have an intensive format with written (research) assignments, class presentations, final papers, written exams, and / or short exercises. For each course a course manual is available in the electronic learning environment Blackboard. In these manuals you will find more detailed information about the content, aims and structure of the course.
Feedback is seen as an essential part of effective learning, so you receive feedback about your progress and accomplishments at multiple points through the course. Feedback is given in a timely manner. This is not only done via classical exams and assignments, but you also receive guidance about how to improve your work to reach aims of the course, addressing difficulties and misunderstanding before final assessments. Also, in several courses you submit drafts for initial (ungraded) feedback before you submit your final assignment.
In addition to general classroom feedback on common strengths and areas of improvement, and the written individual feedback you receive for your work, there are also one-on-one meetings in which you receive elaborate, in-depth personalised feedback on your work (e.g., in the course Preparation for the Research Master's thesis). Also, self-assessment, where you are asked to reflect on your own strengths and weaknesses, is employed (e.g., as part of a training on presentation skills in the second year).
In the second year you can design your own programme and choose 15 EC credits in the field of your interest, such as: data science, survey research, educational measurements, or biomedical research. You can also choose to do an internship. Please note: your electives need to be related to methodology and statistics and will have to be approved by the coordinator.
You can also choose one of our predefined tracks:
- EMOS track (Official Statistics)
- Contemporary Psychometrics Track
- Applied Data Science Track
EMOS Track (Official Statistics)
In this track you will study statistics as it is carried out at statistical bureaus such as Statistics Netherlands and planning bureaus. EMOS stands for European Master in Official Statistics, which is a EUROSTAT initiative. Within this track, you will take the extended elective course EMOS Core Module, taught mainly by Statistics Netherlands. You will also prepare and write your thesis under the supervision of Statistics Netherlands employees.
For more information on the EMOS track, please contact Dr. Bella Struminskaya (firstname.lastname@example.org).
Contemporary Psychometrics Track
In this track you will study statistics and data science as they are applied to data from psychological or educational tests, surveys, and various kinds of new data sources relevant for measuring human behaviour and ability.
You will take the extended elective course Contemporary Psychometrics: Theory and Applications, taught by experts from the University of Twente and Cito, the national institute of educational measurement in the Netherlands. You will also prepare and write your thesis under the supervision of University of Twente or Cito employees.
For more information on the Psychometrics track, please contact Dr. Remco Feskens (Cito) via email@example.com.
Applied Data Science Track
In the Applied Data Science track you will address the challenges for decision making, planning, and knowledge discovery in large collections of diverse data. You will take two courses (7.5 ECTS credits each) in the area of data science: Data Analytics 1: Supervised Learning and Visualisation, and Data Analytics 2: Battling the Curse of Dimensionality.
You can contact the coordinators of the Applied Data Science track via firstname.lastname@example.org for more information.