Statistics C
Course package, Bachelor's level
Expand the information below to show details on how to apply and entry requirements.
Autumn 2025
Autumn 2025,
Uppsala, 100%, On-campus, The course will be taught in English, if needed
- Location
- Uppsala
- Pace of study
- 100%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 1 September 2025–18 January 2026
- Language of instruction
- The course will be taught in English, if needed
- Entry requirements
-
45 credits in statistics
- Selection
-
All qualified applicants will be admitted.
- 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 45,000
- Total tuition fee: SEK 45,000
- Application deadline
- 15 April 2025
- Application code
- UU-26652
Admitted or on the waiting list?
- Registration period
- 22 July 2025–31 August 2025
- Information on registration from the department
Expand the information below to show details on how to apply and entry requirements.
Spring 2026
Spring 2026,
Uppsala, 100%, On-campus, The course will be taught in English, if needed
- Location
- Uppsala
- Pace of study
- 100%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 19 January 2026–7 June 2026
- Language of instruction
- The course will be taught in English, if needed
- Entry requirements
-
45 credits in statistics
- Selection
-
All qualified applicants will be admitted.
- 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 45,000
- Total tuition fee: SEK 45,000
- Application deadline
- 15 October 2025
- Application code
- UU-76652
Admitted or on the waiting list?
About the course package
Statistical Inference and Machine Learning: The course covers methods in statistical inference and machine learning. Topics that are covered include asymptotic methods, simulation, bootstrap, Bayesian methods, non-parametric methods, model selection and evaluation, regularisation methods, non-linear regression and classification. In the course, students work with data using statistical software to carry out a statistical investigation.
Multivariate Analysis: This is a course in applied multivariate statistical methods. The course covers several subjects in multivariate analysis, such as factor analysis and cluster analysis. Statistical software is used throughout the course.
Courses included
Essay/Research Paper, 15 credits
Multivariate Analysis, 7.5 credits
Syllabus
- Syllabus valid from Autumn 2024
- Syllabus valid from Spring 2022
- Syllabus valid from Autumn 2021, version 3
- Syllabus valid from Autumn 2021, version 2
- Syllabus valid from Autumn 2021, version 1
- Syllabus valid from Spring 2020
- Syllabus valid from Spring 2016
- Syllabus valid from Autumn 2007, version 2
- Syllabus valid from Autumn 2007, version 1