This course focuses on statistical analysis of research data, centred around today’s standard method, which involves linear models, especially those with mixed effects (i.e., both “fixed effects” and “random effects” (e.g., participants drawn randomly from a population of people, and often also words or sentences drawn randomly from a language). If you are already familiar with some statistical techniques, you may have seen t-tests, correlation tests, and analysis of variance. During the course, these concepts turn out to be specific simplifying cases of mixed-effects modelling.

You do not need prior knowledge of statistical methods. If you do have such knowledge, you may in fact have to unlearn some internalized ways of thinking.

NB: This is a MA student course with a few extra slots open for PhD's. Participants are expected to attend the full course, which lasts from February to March, and participate in the examinations.