Research Designs in Political and Policy Studies

The very first notion almost everyone learns in their introductory statistics classes is that 'correlation does not imply causation'. Usually, students are presented with several examples of spurious correlations to stress that just because two variables move in tandem, this does not necessarily signal a causal relationship between them. In the everyday practice of statistics teaching, the message this sentence carries has been taken a little too far: it is repeated like a mantra, to criticize every observational study as being unable to detect causation behind statistical association.

The course provides a gentle introduction to statistical analysis in the field of political science. Students who will attend classes, will by the end of the module be able to:
- understand under which assumptions correlation unveils causation in observational studies;
- develop a sound research design and perform multivariate analyses on STATA;
- grasp the improvements introduced by weighting and matching procedures;
- master debates on the necessary conditions for their own inferences on observational data to justify a causal interpretation.

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