Forecasting Methods and Causal Inference for the Social Sciences
Course, Master's level, 2FK065
Spring 2024 Spring 2024, Uppsala, 100%, On-campus, English
- Location
- Uppsala
- Pace of study
- 100%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 21 March 2024–25 April 2024
- Language of instruction
- English
- Entry requirements
-
Fulfilment of the requirements for a Bachelor's degree, from an internationally recognised university. A quantitative research methods course at Master's level of at least 7.5 credits, or 60 credits of statistics at the undergraduate level, or equivalent. 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 12,500
- Total tuition fee: SEK 12,500
- Application deadline
- 16 October 2023
- Application code
- UU-70519
Admitted or on the waiting list?
- Registration period
- 21 December 2023–31 January 2024
- Information on registration from the department
Spring 2024 Spring 2024, Uppsala, 100%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 100%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 21 March 2024–25 April 2024
- Language of instruction
- English
- Entry requirements
-
Fulfilment of the requirements for a Bachelor's degree, from an internationally recognised university. A quantitative research methods course at Master's level of at least 7.5 credits, or 60 credits of statistics at the undergraduate level, or equivalent. Proficiency in English equivalent to the Swedish upper secondary course English 6.
Admitted or on the waiting list?
- Registration period
- 21 December 2023–31 January 2024
- Information on registration from the department
Spring 2025 Spring 2025, Uppsala, 100%, On-campus, English
- Location
- Uppsala
- Pace of study
- 100%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 25 March 2025–29 April 2025
- Language of instruction
- English
- Entry requirements
-
Fulfilment of the requirements for a Bachelor's degree, from an internationally recognised university. A quantitative research methods course at Master's level of at least 7.5 credits, or 60 credits of statistics at the undergraduate level, or equivalent. 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 12,500
- Total tuition fee: SEK 12,500
- Application deadline
- 15 October 2024
- Application code
- UU-70519
Admitted or on the waiting list?
Spring 2025 Spring 2025, Uppsala, 100%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 100%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 25 March 2025–29 April 2025
- Language of instruction
- English
- Entry requirements
-
Fulfilment of the requirements for a Bachelor's degree, from an internationally recognised university. A quantitative research methods course at Master's level of at least 7.5 credits, or 60 credits of statistics at the undergraduate level, or equivalent. Proficiency in English equivalent to the Swedish upper secondary course English 6.
Admitted or on the waiting list?
About the course
The course aims to deepen the knowledge of quantitative social science methodology that students have acquired during undergraduate studies. The aim is to develop students' ability to use forecasting and causal inference methods in order to answer a research question and test theoretical arguments. The course offers training in how to design, estimate, and interpret common methods within forecasting and causal inference. Key techniques covered include Monte Carlo simulation, randomization inference and prediction. There will be a focus on understanding the assumptions and goals of different methods and evaluating their strengths and weaknesses. To support students' practical application, the course includes the use of statistical software.
Reading list
No reading list found.
Contact
- Ingalill Blad Ögren
- ingalill.blad-ogren@pcr.uu.se
- +46 18 471 23 49