Master's programme
The Master's programme in statistics and data science gives a sold foundation in statistical theory, as well as deeper knowledge in areas such as econometrics, causal inference, psychometrics and biostatistics. Students get strong skills in being able to critique and interpret data from different areas. Students with a degree from the Master's programme in statistics and data science are well prepared for work both in the private and public sector, as well as for continued studies within PhD programmes. Apart from courses in our own Master's programme, we also give courses within the Master's programme in social sciences.
For questions regarding studies in statistics, arrangement of courses as well as advice on choice of courses and requirements, turn to the study counsellor.
Master's programme in statistics and data science, more information and application.
Alumni overwhelmingly positive to the Master’s programme in statistics
Courses in the Master's Programme in Statistics and Data Science
Each course has a course syllabus. The syllabus provides information about the entry requirements, learning outcomes, content, instruction and assessment. Syllabi are approved by the faculty or department offering the course and are subject to change from semester to semester. Reading lists are appended to each syllabus.
Semester 1
- Linear Algebra for Statisticians (7.5 credits)
- Probability Theory (7,5 credits)
- Statistical Programming with R (7.5 credits)
- Inference (7.5 credits)
Semester 2
- Advanced Econometrics (7.5 credits)
- Multivariate Statistical Analysis (7.5 credits)
- Causal inference (7.5 credits)
- Structural Equation Models (7.5 credits)
Semester 3
Choose two out of the following three courses for the first half of the semester:
- Bayesian Statistics and Data Analysis (7.5 credits)
- Generalised Linear Models (7.5 credits)
- Time Series Econometrics (7.5 credits)
Choose two out of the following three courses for the second half of the semester:
- Analysis of Survival Data, 7.5 credits
- Financial Econometrics (7.5 credits)
- Machine Learning (7.5 credits)
Semester 4
One-year master
There is also an opportunity to take a one-year Master's degree. In that case, a 15 credit Master's thesis is written during the second semester.
Courses in statistics within other Master's programmes and freestanding courses
Alumni overwhelmingly positive to the Master’s programme in statistics
An alumni survey was sent to all graduates from the Master’s programme in statistics at Uppsala University, with respondents being asked questions about the skills they learned at the programme in light of their labour market experience as well as information about their previous and current jobs.
Respondents to the survey were overwhelmingly positive with 98% reported being happy that they studied on the programme. The labour market prospects for graduates from the programme are exceedingly bright. Most respondents reported a seamless transition to the labour market, with a majority getting their first job before even finishing the programme and 95% having a job within five months of graduation.