For Harvard students: Lecture: Mondays 2:00-4:00 (CGIS S-010)
Section: Wednesdays 6pm and 7pm (CGIS K-354)
For others: register here for online access (for credit or auditing).

Gary King

Phone: 617-500-7570

Administrative Assistant: 617-495-9271

Office: 1737 Cambridge Street (CGIS), K313

Stephen Pettigrew

Teaching Fellow

Office Hours:

Mondays 11:00-1:00 (CGIS-K Cafe)

Solé Prillaman

Teaching Fellow

Office Hours:

Fridays 2:00-4:00 (CGIS-K Cafe)

For students who've taken a course in linear regression (such as Harvard's Gov2000), we give you the tools to learn new statistical methods or even build them yourself.  We focus on practical methods useful for real social science research, from learning methods to publication.  We aim to give you two types of skills.

First, we show how to develop new approaches to research methods, data analysis, and statistical theory.   More advanced statistical theory is not required when data and variables follow standard assumptions. Since this is not usually the case in most of the social sciences, we often cannot always use ready-made statistical procedures developed elsewhere and for other purposes. We teach the underlying theory of inference (which, at its most fundamental is merely using facts you know to learn about facts you don't know); once understood, we can easily “reinvent” known statistical solutions to accommodate social science data, learn new techniques as they are invented, or even invent original approaches when required. We'll show you how to read an original scholarly article describing a new statistical technique, implement it in computer code, estimate the model with relevant data, understand and interpret the results, and present and explain the results to someone unfamiliar with statistics.

Second, students will learn how to contribute novel substantive contributions to a scholarly literature. A substantial portion of those who complete the course publish a revised version of their class paper in a scholarly journal. For most students, this is their first professional publication. For some of the papers from previous years, see the Gov 2001 Dataverse.

Most of the course will be lecture-based, and several more collaborative approaches will be used too. For resources and tools, see the section Learning Resources.