Information for students, faculty and staff regarding COVID-19. (Updated: 21 October 2020)
Do you want to hone your analytical powers, learn to process reams of data and make this data sing? In this digital age, with an explosion in both the amount of data collected and in the computational power at our disposal, there is enormous demand across all segments of the economy for highly trained statisticians. Our programme will stretch your mind, increase your statistical prowess and equip you with a solid theoretical foundation for tackling the data-driven challenges of the future.
You will be part of a human-sized Master's programme hosted by the Department of Mathematics and Mathematical statistics. The small-scale of the programme allows for individualised learning, and for richer and more personal interactions between students and teachers, and is one of its main attractions. All incoming Master students are assigned a mentor from one of our main research groups – Biostatics/bioinformatics, Functional data analysis & spatial statistics, and Statistical learning & inference. The mentor follows the student through the programme, giving advice on the choice of courses and thesis topics, as well as on applications to PhD programmes.
Beyond the programme's core courses and thesis projects, there is a great flexibility about choosing courses from closely related fields such as mathematics and computer science. Teaching on the programme consists of a mixture of traditional lectures, seminars and individual supervision on the one hand, and of extensive courses and projects based in a computer lab setting on the other hand, in which one learns to master advanced data analytics and statistical software (R, Minitab, SPSS, ...). All teaching on the programme is done in English and by active researchers with a long experience of statistical analysis and statistical consulting.
Should you wish to, you also have the opportunity of taking part in a semester-long exchange abroad at partner mathematical statistics departments in Italy, France, Spain, the UK, China, South Korea and Kazakhstan as part of your studies.
The programme's greatest draw is its close connection to the life of the research groups in the department, which we hope you will take full advantage of. As a student on the programme, you will be able to work on research and thesis projects with some of our highly successful researchers, and to use the mentoring system as a gateway into the world of research.
Living as we do in the age of the data-driven economy, statistical skills are in high demand on the labour market. In addition some of our core courses (and much of our research) lie in exciting "hot topic" areas such as machine learning, artificial intelligence, network science and big data. The employment prospects of our graduates are thus excellent.
Finally, Umeå provides a highly attractive environment for studying. It is a young and fast growing city of around 120 000 inhabitants, of whom over 35 000 are students. This makes for a rich cultural life, with many pubs, cafés, restaurants, concerts and festivals. The city is home to Norrlands Opera and to Bildmuseet, a museum of contemporary art and visual culture. In 2014, Umeå shared with Riga the distinction of being the European capital of culture.
The city is small, extremely safe and well-run, with an extensive network of bicycle paths allowing its denizens to cycle all year round. It is surrounded by beautiful nature – from the Umeå river, which freezes over in winter and becomes criss-crossed with cross-country skiing tracks, to Nydala lake and the Gammlia forest within the city limits, and to the vast and largely unspoiled countryside of forests, lakes and seashore just outside it. And of course studying in Umeå allows you to experience the Swedish way of life, with its well-delineated seasons and traditions, from Sankta Lucia in the dark of December to Midsommar in the overflowing light of June, with coffee and cinnamon buns throughout.
Courses at the advanced level:
Advanced Inference Theory
Advanced Probability Theory
Big Data and high-dimensional data analysis
Research in the Mathematical Sciences
Design of Experiments and Advanced Statistical Modelling
Multivariate Data Analysis
Statistics in Genetics
Time Series Analysis and Spatial Statistics
There is a lot of flexibility to mix and match both statistical courses from the programme and relevant courses from mathematics and computer science. Your mentor will help and advise you on choosing a tailor-made set of courses from the available options.
Research experience/Thesis work:
Research project in Mathematical Statistics
Thesis Project for the Degree of Master of Science in Mathematical Statistics (one year)
Thesis Project for the Degree of Master of Science in Mathematical Statistics
Graduates of a master's programme in statistics have a wide range of opportunities available to them. Statistical skills are highly sought-after, for example, in IT, in the insurance sector, in the pharmaceutical industry and medical research more generally, in many government agencies, and in any context where large reams of data are to be analysed. And of course a master's degree is a natural and necessary preparation for entering a PhD programme and pursuing a career in statistical research within academia.