The course is designed to provide scholars with a basic understanding of multilevel (a.k.a. hierarchical or mixed) models. Special attention is given to the translation of theoretical expectations into statistical models, the interpretation of results in multilevel analyses and the general use and misuse of multilevel models in the social sciences. While the course is predominantly designed to give you the knowledge of multilevel regression modeling, it does also arm you with the basic tools to run multilevel models in R. Applications will include models with continuous and limited dependent variables in hierarchical, longitudinal and cross-classied nesting situations and other advanced topics. The goal of the course is to oer a basic introduction and the foundation for students to start using and critically assessing multilevel models and also have the ability to independently discover and master advanced multilevel statistical topics. Upon completion the students will have a basic conceptual understanding of multilevel modeling and its statistical foundations. Students will be able to critically assess the appropriateness of such techniques in their own and other people's research and conduct multilevel modeling themselves to the highest academic standards.