Math 591 -- Algebraic Statistics

Spring 2015,  TuTh 8:30--9:45 AM, SAS 2106

Instructor: Seth Sullivant, office: 3114 SAS Hall, email:

Syllabus: Syllabus

Office Hours: Tu 10:00- 11:00, W 2:00-3:00, Or by appointment

Text: M. Drton, B. Sturmfels, S. Sullivant. Lectures on Algebraic Statistics, Birkhauser.

Suggested Text: L. Pachter and B. Sturmfels. Algebraic Statistics for Computational Biology. Cambridge University Press.

Prerequisites: Good preparation in undergraduate mathematics (linear algebra, abstract algebra, analysis).

Course Description: Algebraic statistics concerns the use of tools from algebraic geometry, symbolic computation, and combinatorics to address problems in statistics, theoretical probability, and their applications. This course will be an introduction to algebraic statistics, highlighting some of the most important results and major areas of active research. Some topics to be covered: conditional independence and graphical models, Markov bases, maximum likelihood estimation, identifiability problems, singular learning theory, and applications to mathematical biology.

Schedule: Is available here.

Homework: Will be posted here occasionally.

Final Project: Grade will be determined by a final project in algebraic statistics. Information about the final project is available here.

LateX Resources: