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Quantitative Methods I



The course builds on the knowledge gained in introductory statistics courses and deepens students’ understanding of the key techniques for testing causal hypotheses with cross-sectional data. The techniques covered include among others:

  • correlation (parametric and non-parametric), with a focus on meaning and limitations of the ‘statistical significance’;

  • Ordinary least-squares regression with a focus on testing mediation, moderation and interaction effects;

  • logistic regression with a focus on how to interpret coefficients;

  • factor analysis
    Particular attention is based on rigorous check of assumptions of the techniques and on interpretation and presentation of the results. The course is based on the statistical program ‘R’.

Methods of Instruction

The course will use a mix of lectures, and class discussions of assigned literature and of home-assignments.


4 assignments (10% each) and a final paper (60%)

Study material

Field, Andy, Jeremy Miles, and Zoë Field. 2012. Discovering Statistics Using R. London: Sage
A selection of articles (announced on Blackboard).


See Preliminary Info