Entry requirements

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.

Aims

The overall aim of the Master's programme in Statistics and Data Science is for the students to learn the tools and analytical skills necessary to perform theoretically well-founded and practically relevant data analysis. To do so, the students need a solid foundation in statistical theory, as well as an understanding of the connection between statistical theory and applied data analysis. They should also be able to communicate statistical concepts and results, both orally and in writing. The programme prepares the students to work as statisticians and data analysts in both the private and public sector, but is also preparatory for PhD programmes in statistics.

Learning outcomes

Goals Expressed as Expected Outcomes

Upon completing the programme students are expected to: 

• understand the principles of estimation and inference that underpin statistical theory, 
• be able to evaluate statistical models and critically asses their relevance for practical applications, 
• understand the different types of research questions that arise in applied statistical work and to be able to choose appropriate statistical methods for different research questions, 
• be familiar with various steps of data analysis such as designing a study, handling data of different forms, performing statistical analyses and completing written oral reports, 
• be able to communicate results from statistical analyses to both statisticians and non-statisticians, 
• be able to understand, interpret and critically review scientific articles, 
• understand and reflect on the ethical questions that arise in statistical work and data analysis,  
• be able to identify their own need of further knowledge and to take responsibility for their own learning.

Layout of the programme

The programme begins with preparatory courses, aimed at giving students the tools which are needed for the programme. Then follows theoretical courses giving students a solid foundation in statistical theory, as well as courses in a number of specialized areas, where it may also be possible to choose which courses to take. During the last semester, the master thesis is written.

Instruction

The programme is grounded in science and is tied to research, and students are provided with opportunities to continuously develop their methodological competence and a scientific approach. Students are expected to assume more and more responsibility for their own learning the further they progress in the programme and to successively acquire occupationally relevant and research-based knowledge and skills.

The specific teaching formats vary between the different courses. The standard formats include lectures, laboratory exercises, tutorials and/or seminars. The language of instruction is English.

Degree

The programme leads to a two-year Master's degree comprising 120 higher education credits in the major field of statistics (Degree of Master of Social Science, 120 credits). The two-year Master's degree requires 60 higher education credits in the major field, at least 30 higher education credits of which comprise an independent degree project.

The prorgamme can also lead to a one-year Master's degree comprising 60 higher education credits in the major field of statistics (Degree of Master of Social Science, 60 credits). The one-year Master's degree requires 30 higher education credits in the major field, at least 15 higher education credits of which comprise an independent degree project.