Analysis of Survival Data
Course, Master's level, 2ST072
Autumn 2023 Autumn 2023, Uppsala, 50%, On-campus, The course will be taught in English, if needed
- Location
- Uppsala
- Pace of study
- 50%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 2 November 2023–14 January 2024
- Language of instruction
- The course will be taught in English, if needed
- Entry requirements
-
120 credits including 90 credits in statistics, or 120 credits including 60 credits in statistics and 30 credits in mathematics and/or computer science.
- 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 12,500
- Total tuition fee: SEK 12,500
- Application deadline
- 17 April 2023
- Application code
- UU-26627
Admitted or on the waiting list?
- Registration period
- 27 July 2023–27 August 2023
- Information on registration
Autumn 2024 Autumn 2024, Uppsala, 50%, On-campus, English
- Location
- Uppsala
- Pace of study
- 50%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 6 November 2024–19 January 2025
- Language of instruction
- English
- Entry requirements
-
120 credits including 90 credits in statistics, or 120 credits including 60 credits in statistics and 30 credits in mathematics and/or computer science.
- 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 12,500
- Total tuition fee: SEK 12,500
- Application deadline
- 15 April 2024
- Application code
- UU-26627
Admitted or on the waiting list?
About the course
Survival data consists of time to the occurrence of a certain event, and data are often censored (the event does not occur for all individuals). Modelling and analysis of such data, therefore, require special methods which are studied in this course.