Skip over navigation

Course Offerings

Course Evaluation Results

Course Details

Spring 2017-2018
* SOC 401 (QR)   No Audit

Advanced Social Statistics

Matthew J. Salganik

Introduces theories of inference underlying most statistical methods and how new approaches are developed. The first half of the course covers maximum likelihood estimation and generalized linear models. The second half covers a number of topics useful for applied work including missing data, matching for causal inference and hierarchical models. The course concludes with a project replicating and extending a piece of work in the scholarly literature.

Sample reading list:
Gary King, Unifying Political Methodology:
John Fox, Applied Regression Analysis and Generalized Linear Models
Norman Matloff, The Art of R Programming: A Tour of Statistical Software
Blitzstein and Hwang, Introduction to Probability

Reading/Writing assignments:
Weekly problem sets and a final paper.

Paper in lieu of Final - 50%
Class/Precept Participation - 10%
Problem set(s) - 40%

Prerequisites and Restrictions:
SOC 400 or comparable course..

Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
40748 S01 09:30:00 am - 10:50:00 am T Th   Wallace Hall   165   Enrolled:4 Limit:12
40747 B01 10:00:00 am - 11:50:00 am F   Wallace Hall   165   Enrolled:4 Limit:12