Methodology and Statistics for the Behavioural, Biomedical and Social Sciences

What characterizes a good research question, and how can we align this with data collection and statistical analyses to obtain meaningful results? How should we deal with missing data in our analysis? What is the best way to design a clinical trial to test new medical treatments? How can data integration techniques enhance research and official statistics data? Can we improve statistical techniques by including prior knowledge? How can we make causal inferences using observational data? What are the best practices for collecting reliable data on sensitive issues like personal income or medication? How can we fairly assess which machine learning technique detects fraud best? And how can we effectively discuss all of this within an interdisciplinary team with varying data literacy?

State-of-the-art research in Methodology and Statistics

Modern society is highly data-driven. Everything is monitored and measured, yet there are major challenges to finding optimal ways to design research, analyse data, extract the most valuable information from data, and communicate the results. This two-year Master’s programme trains students to become researchers as well as data scientists and data analysts who can bridge the gap between fundamental statistics underlying modern data analysis and empirical research in the behavioural, biomedical, and social sciences – both within and beyond academia.

Programme objective

In this programme, you are trained to solve real-world problems through the analysis of data and the development of new methods. In pursuing this goal, you will learn to:

• Define a clear research question, and link this to a particular research design and statistical analysis.
• Understand how data collection, sampling, experimental design, and measurement have an impact on data quality, analyses, and conclusions.
• Work with a broad array of statistical and machine learning methods for description, explanation, prediction, and causal inference.
• Implement statistical and machine learning methods using various software packages.
• Write code and set up computer simulations to assess the performance of different analysis approaches and develop innovative methods that improve upon state-of-the-art techniques.
• Communicate and collaborate in multidisciplinary teams of researchers and practitioners to plan, collect, explore, analyse, summarise, and present data products in a reproducible, accessible, and open way.

Our students are the next generation of statisticians, data analysts, and data scientists. As such, we aim to provide a rich learning environment, that will help you fulfill your potential. We work in small groups so there is plenty of room for personal attention and our lecturers are top scientists. So rest assured you will learn from the best!

Cooperation within and outside the academic world

The programme combines the research expertise and focuses of the following departments:

• Department of Methodology and Statistics, Utrecht University
• Department of Biostatistics, University Medical Center Utrecht
• Department of Research Methodology Measurement and Data Analysis, University of Twente
• Statistics Netherlands
• Cito

This cooperation results in a broad choice of thesis topics.

World-class university in a lively student city

Choosing Utrecht University means choosing one of the best universities in the country with several renowned international rankings  and twelve Nobel Prize laureates. 

Located in the middle of the Netherlands, Utrecht is a medieval city with a centre small enough to explore on foot, yet large enough to host world-class festivals, fashionable shops, modern architecture and fascinating museums. Find more about what student life is like in Utrecht!