This is a course in quantitative political science. The aim is to provide a rigorous foundation for students interested in applying quantitative methods in their own research. The rst part of the course provides a thorough treatment of generalized linear models. We will cover both standard models and their hierarchical extentions. The main text for this part is Long, S. J. (1997). Regression Models for Categorical and Limited Dependent Variables. SAGE, London. The second section of the course covers event-history models. Here, the main text will be Box-Ste ensmeier, J. M. and Jones, B. S. (2004). Event History Modeling: A Guide to Social Scientists. Cambridge University Press. We will use R, a free statistical programming language. It is available at www.r-project.org. Here, you will also nd a lot of useful information about R. I also recommend you to use Rstudio, www.rstudio.org for running R on your computer. I use LATEX to typeset my papers and presentations. It works great in combination with R and Rstudio. If you are serious about learning R, study Matlo , N. (2011). The Art of R Programming: A Tour of Statistical Design. No Starch Press: San Fransisco. An introduction to LATEX can be found here: http://ctan.uib.no/info/lshort/english/lshort.pdf. The course aims to teach students how to do reproducable research. In order to integrate LATEX and R, we will use knitr, http://yihui.name/knitr/. Each week will have two lectures and one computer class. One lecture will be devoted to the statistical properties of the model, assumptions and generalization. The second lecture will focus on estimation and interpretation of the estimates obtained from the model. The purpose of the computer classes is to develop programming tools to become a productive quantiative political scientist.