Carnegie Mellon University

Statistics/Public Policy Joint Ph.D. Degree

Our Department offers a joint program in collaboration with the Heinz College of Information Systems and Public Policy, leading to a Ph.D. in Statistics and Public Policy. This five-year program provides students with comprehensive preparation at the Ph.D. level in both statistics and public policy.

The curriculum draws on existing courses in both Statistics and Heinz College, recognizing that selected courses can meet, simultaneously, the usually-separate objectives of the Ph.D. programs in Statistics and Public Policy. Critical to the success of the joint program is the close collaboration among faculty members in Statistics and Heinz College. While students will have separate faculty advisors in Statistics and in Heinz College, their progress will be regularly assessed by a joint group of faculty.

Students in this program have split TA duties between Statistics and Heinz College, being supported one semester each academic year from each unit.


Students in this program are subject to all of the core Ph.D. requirements.

The actual curriculum for any given student will be tailored to her or his interests and needs, but the general strategy is similar: to meld the two sets of Ph.D. requirements into a coherent and useful set of courses, with similar core items. The first four semesters cover the main courses for the Ph.D. in Statistics while simultaneously introducing the student to the core disciplines at Heinz College. In the fourth semester, students begin work on the second Heinz research paper, which also satisfies the Advanced Data Analysis (ADA) requirement in Statistics.

The Path to the Ph.D.

Below is one possible three-year plan of study for students to complete the coursework requirements. Adjustments can be made for cases where students need to build additional background in a particular area.

Year One

Fall Semester

  • 36-699: Immigration to Statistics
  • 36-707: Regression Analysis
  • 36-705: Intermediate Statistics
  • 90-908: Microeconomics
  • 90-901: Heinz Ph.D. Seminar I

Spring Semester

  • 36-757: Advanced Data Analysis I
  • 36-709: Advanced Statistical Theory I
  • 36-708: Statistical Methods in Machine Learning
  • 90-902: Heinz Ph.D. Seminar II

Year Two

Fall Semester

  • 36-758: Advanced Data Analysis II
  • 36-750: Statistical Computing
  • 90-907: Econometric Theory and Methods
  • 90-918: Heinz Ph.D. Seminar III

Spring Semester

  • Complete 1st Heinz/ADA paper
  • Heinz curriculum requirements elective
  • Start 2nd Heinz paper

Year Three

Fall Semester

Spring Semester

  • Complete 2nd Heinz/ADA paper
  • Begin work toward thesis proposal