This course begins by reviewing linear models, covering their basic assumptions, their estimation, the interpretation of results, and diagnosing violations of assumptions. From there, we move to reviewing a range of different models used in political science where the traditional linear regression assumptions are violated, including different types of logistic regression, panel and event analysis for data observed over time, and others. Issues of model choice, specification, and replication are emphasised with examples from political science and international relations.