Master's Programme in Statistics and Data Science
120 credits

The ability to understand, interpret and analyse data is central for many qualified jobs in the private and public sector, organisations and within research. The Master's programme in Statistics and Data Science gives a solid foundation in statistical theory and a broad toolbox of methods for working with data in many different application areas. A Master's degree in Statistics not only opens up a wide array of opportunities in working life, but also prepares you for a research career.
Autumn 2023 Autumn 2023, Uppsala, 100%, On-campus, English
- Location
- Uppsala
- Pace of study
- 100%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Start date
- 28 August 2023
- Language of instruction
- English
- Entry requirements
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Academic requirements
A Bachelor's degree, equivalent to a Swedish Kandidatexamen, from an internationally recognised university.
Also required is 90 credits in statistics, or 60 credits in statistics and 30 credits in mathematics and/or computer science
Language requirements
Proficiency in English equivalent to the Swedish upper secondary course English 6. This requirement can be met either by achieving the required score on an internationally recognised test, or by previous upper secondary or university studies in some countries. Detailed instructions on how to provide evidence of your English proficiency are available at universityadmissions.se.
- Selection
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Students are selected based on an overall appraisal of previous university studies and a statement of purpose.
Tuition fee-paying students and non-paying students are admitted on the same grounds but in different selection groups.
- Fees
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If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
- Application fee: SEK 900
- First tuition fee instalment: SEK 50,000
- Total tuition fee: SEK 200,000
- Application deadline
- 16 January 2023
- Application code
- UU-M2660
- Additional information
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In addition to the general supporting documents, you also need to submit the following programme-specific documents:
- a summary of your of your Bachelor's thesis or equivalent (1–2 pages)
- a statement of purpose (1–2 pages).
Check the application guide for information on how to apply and what other supporting documents you need to submit.
About the programme
In today's society, the quantity of information and data that are available is enormous. To be able to sort out what is relevant from this information, data must be analysed and summarised in ways which highlight what is important while filtering out that which is unnecessary.
Statistics is the science that has been developed to achieve this goal and its relevance has never been greater than it is today, as statistical methods are used in all different areas of society. The goal of the Master's programme in Statistics and Data Science is to give you both the depth and breadth which is required to work with qualified tasks within a wide array of areas. The programme also prepares you for future PhD studies.
The statistical methods taught in this programme will answer questions such as:
- What is the effect of a new medical treatment, and how strong is this effect?
- Who will win the upcoming election?
- What policies will affect the unemployment rate?
- How can images and texts be automatically grouped and classified?
- How should the graphical user interface for a web page or app be designed for customers to be as satisfied as possible?
Compared with the Master's programme in Data Science, the Master's programme in Statistics and Data Science focus mainly on the collection and analyses of data, where the emphasis is on developing analytical skills in order to answer descriptive, predictive or causal questions in different application areas. This competence allows our graduates to work as highly qualified experts in the industry, public institutions and research. Students get a solid foundation in programming to be able to put their expertise to use, but there is less emphasis on how to build infrastructure to deal with large-scale data."
The early courses in the programme give a solid foundation in statistical theory and programming. In the subsequent courses, you will learn how to use statistical methods to deal with real and important problems. Prominent researchers teach within the courses, which means that the content comes directly from the international research frontier. The progression in the programme entails a higher level of intellectual maturity and deeper insights into the complexities of the subject. This, together with the ability to integrate knowledge and skills and to independently formulate and solve problems, is demonstrated in your Master's thesis.
Degree
The programme leads to the degree of Master of Social Science (120 credits) with Statistics as the main field of study. After one year of study, it is possible to obtain a degree of Master of Social Science (60 credits).
Content
The programme comprises four semesters of full-time study. The programme starts with the courses "Linear Algebra for Statisticians" and "Statistical Programming with R", which aim to give you skills in mathematics and programming that are necessary for studies on the programme, as well as the courses "Probability Theory" and "Inference", which aim to consolidate and deepen the theoretical understanding of randomness and how to draw conclusions from data containing random variation.
For the rest of the first three semesters, more specialised courses are given where you learn how to handle and analyse data. Here there are also some opportunities to choose which courses to take. In the third semester, it is also possible to do an internship worth 30 credits.
The last semester you write a Master's thesis worth 30 credits. It is not unusual for the thesis to be written in cooperation with a company or a public institution. If you wish to conclude your studies after one year, you replace coursework worth 15 credits during the second semester with a 15-credit Master's thesis.
Courses within the programme
Semester 1
- Linear Algebra for Statisticians, 7.5 credits
- Probability Theory, 7.5 credits
- Inference, 7.5 credits
- Statistical Programming with R, 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
You 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
You 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
Alternatively, you can do an internship during the whole semester, 30 credits
Semester 4
- Master's thesis in Statistics, 30 credits
Learning experience
The Master's Programme in Statistics and Data Science is an international education and is taught in English. Instruction is mainly in the form of lectures, seminars and tutorials with elements of assignments.
In a seminar, you present your ideas and discuss with your classmates a course book or other study material that you are required to read before the seminar; while the teacher usually only moderates the discussion. The aim is to develop critical thinking and collaborative skills, which are required for your future career development. All the students are expected to be active participants in all forms of discussions.
Examination of the courses is in the form of written exams, assignments and seminars.
Courses in the programme are generally 7.5 credits and are given in parallel, each at half speed. During the programme, you will also have the opportunity to experience a semester of supervised training at a public authority, an organisation or a company that can provide work assignments of value to your selected specialisation and future career plans. The traineeship semester comprises 30 credits.
The programme is offered in Uppsala.
Career
The Master's Programme in Statistics and Data Science prepare you for a successful career, both nationally and internationally. As a statistician, data analyst or data scientist you generally work closely with subject matter experts within different areas, and your role is to have knowledge on how to collect, analyse and interpret data.
Knowledge and skills of working with data are in very high demand in the labour market, and due to its methodological breadth, the Master's Programme in Statistics and Data Science gives you excellent opportunities to be hired in a wide range of fields, both in the private and public sectors. With an exam, you are also eligible for PhD studies, which open up the possibility for an academic career as researcher in statistics.
An alumni survey was conducted among our former master students during 2021. This survey showed that the career opportunities for our students are excellent. A majority received a job even before they finished their degree, and 95 per cent had a job within five months after receiving their degree. Most alumni also reported that they had a qualified job which required a Master's degree. The many opportunities created by the programme can also be seen based on the different jobs the alumni have. For instance, they work in private companies in the finance, tech and life science industries, but also in government authorities and universities.
Career support
During your time as a student, UU Careers offers support and guidance. You have the opportunity to take part in a variety of activities and events that will prepare you for your future career.
Is this programme right for you?
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