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Causal inference

  • Number of credits 7.5 credits
  • Level Master’s level
  • Starting Autumn Term 2023

About the course

Causal inference is the goal of many empirical studies in the health and social sciences. In a causal analysis, a causal parameter is formally defined and the underlying assumptions are explicitly stated. These assumptions clarifies the differences between experimental data and observational data for making causal conclusions. In the course we focus on two dominating approaches for causal analyses, i) the potential outcomes framework and ii) structural analyses (graphical models). We learn the foundations for these two frameworks as well as methods for estimation of causal effects in experimental and observational studies. Data-examples are given throughout the course and practical problem solving and data analyses are carried out in parallel with the theoretical material.

Application and eligibility

Causal inference, 7.5 credits

Det finns inga tidigare terminer för kursen Autumn Term 2023 Visa tillfällen för efterkommande termin

Starts

31 October 2023

Ends

14 January 2024

Study location

Umeå

Language

English

Type of studies

Daytime, 50%

Required Knowledge

Univ: 90 credits (hp) in statistics and/or mathematical statistics, or equivalent. Proficiency in English equivalent to Swedish upper secondary course English B/6
 

Entry requirements

Selection

Academic credits Applicants in some programs at Umeå University have guaranteed admission to this course. The number of places for a single course may therefore be limited.

Application code

UMU-27800

Application

Application deadline was 17 April 2023. The application period is closed.

Application and tuition fees

As a citizen of a country outside the European Union (EU), the European Economic Area (EEA) or Switzerland, you are required to pay application and tuition fees for studies at Umeå University.

Application fee

SEK 900

Tuition fee, first instalment

SEK 13,700

Total fee

SEK 13,700

Contact us

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Contactpersons for the course are:
Study advisor, Department of Statistics, Umeå School of Business, Economics and Statistics, Umeå University