Courses Alex Teaches

1 Political Science 270: Math and Probability Foundations

1.1 Introduction

PS270 is a (re)introduction to core math and probability concepts for first year political science PhD students. Topics covered in the course include calculus, optimization, linear algebra, and probability. In addition, we will spend time getting you up and running using the technical software that you will use the rest of your career. The Syllabus is located here.

2 Political Science 204b: Research and Methodology

The required first year PhD course in statistics. This course is an introduction to the use of quantitative methods to study political events. This couse builds on the math and probabilty foundation laid in Poli 270. We will cover more probability, hypothesis tests and the linear algebra heart of regression. (Instructor Fall 2014, Lab Instructor Fall 2013, Fall 2012)

3 Political Science 271: Maximum Likelihood Estimation

3.1 Introduction

This course moves beyond the linear model of PS 204 to cover the theoretical basis for maximum likelihood estimation (MLE). Particular focus is placed on the application of these models to political science data. Ordinal and count models, duration and survival models, time-series cross-sectional data, as well as likelihood and bayesian concepts will be covered. This is your swiss-army knife.

3.3 Notes from Professor Langche Zeng

Date: 2015-08-04 Wed

Author: D. Alex Hughes

Created: 2015-09-07 Mon 21:46

Emacs (Org mode 8.2.10)