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Not available in 2023/24
DV560      Half Unit
Bayesian Reasoning for Qualitative Social Science: A modern approach to case study inference

This information is for the 2023/24 session.

Teacher responsible

Dr Tasha Fairfield CON 6.02

Availability

This course is available on the MPhil/PhD in International Relations and MRes/PhD in International Development. This course is available with permission as an outside option to students on other programmes where regulations permit.

Students will be selected for DV560 based on a written statement of interest (max 150 words).  Priority will be given to students on the programs listed above, if demand exceeds places.

Course content

The way we intuitively approach qualitative case research is similar to how we read detective novels.  We consider various different hypotheses to explain what occurred—whether the emergence of democracy in South Africa, or the death of Samuel Ratchett on the Orient Express—drawing on the literature we have read (e.g. theories of regime change, or other Agatha Christie mysteries) and any salient previous experiences we have had.  As we gather evidence and discover new clues, we continually update our beliefs about which hypothesis provides the best explanation—or we may introduce a new alternative that occurs to us along the way.

 

Bayesianism provides a natural framework that is both logically rigorous and grounded in common sense, that governs how we should revise our degree of belief in the truth of a hypothesis—e.g., "mobilisation from below drove democratization in South Africa by altering economic elites’ regime preferences," (Wood 2001), or "a lone gangster sneaked onboard the train and killed Ratchett as revenge for being swindled"—given our relevant prior knowledge and new information that we obtain during our investigation.  Bayesianism is enjoying a revival across many fields, and it offers a powerful tool for improving inference and analytic transparency in qualitative research.

 

This course introduces basic principles of Bayesian reasoning with the goal of helping us leverage our common-sense understandings of inference and hone our intuition when conducting causal analysis with qualitative evidence.  We will examine the foundations of Bayesian probability as well as concrete applications to single case studies, comparative case studies, comparative historical analysis, and multi-methods research.  Students will practice applyi