Data Visualisation and Statistics for Language Sciences
Course, Master's level, 5LN150
Expand the information below to show details on how to apply and entry requirements.
Autumn 2026 Autumn 2026, Uppsala, 50%, On-campus, English
- Location
- Uppsala
- Pace of study
- 50%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 31 August 2026–8 November 2026
- Language of instruction
- English
- Entry requirements
-
120 credits including 90 credits in linguistics or another language subject. Proficiency in English equivalent to the Swedish upper secondary course English 6.
- Selection
-
Higher education credits (maximum 285 credits)
- Fees
- 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.
- First tuition fee instalment: SEK 14,250
- Total tuition fee: SEK 14,250
- Application deadline
- 15 April 2026
- Application code
- UU-57710
Admitted or on the waiting list?
- Registration period
- 3 August 2026–30 August 2026
- Information on registration from the department
Autumn 2026 Autumn 2026, Uppsala, 50%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 50%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 31 August 2026–8 November 2026
- Language of instruction
- English
- Entry requirements
-
120 credits including 90 credits in linguistics or another language subject. Proficiency in English equivalent to the Swedish upper secondary course English 6.
Admitted or on the waiting list?
- Registration period
- 3 August 2026–30 August 2026
- Information on registration from the department
About the course
In this course, you will learn the theory and practice of carrying out empirical research on language. The theoretical part of the course will be research design: the formulation of clear and practical research questions and the critical evaluation of the research design of published papers. The focus will be on applications to sociolinguistic and typological research, although the methods are applicable to other linguistic (and non-linguistic) domains.
The practical part of the course will include an introduction to programming in the statistical computer language R. During the computer labs you will learn all the stages of data analysis: loading data from outside sources, manipulating data into appropriate forms, visualising data, performing simple statistical tests, and sharing and archiving results.