The course is aimed at providing the students with the basic practical skills for running both frequentist and Bayesian statistics, after a brief theoretical overview of the latter. The teacher will try to tackle the main issues met by researchers when analyzing data, both in exploratory and in confirmatory research. Examples will span from elementary statistical objects (t-test, ANOVA, etc.) to more complex estimation procedures (simple linear regression, multiple regression, Mixed Linear Models, etc.). Basic (master-degree level) understanding of statistics is required in order to apply more complex concepts and analyses.

Suggested readings

McElreath (2016, 2020).

Statistical Rethinking. https://xcelab.net/rm/statistical-rethinking/