At Carnegie Mellon University, I am part of the joint PhD program in statistics and public policy. This program combines the requirements and training from the statistics department and the school of public policy and management at Heinz College.
If you are interested in the joint statistics-Heinz program, this information might be useful to you.
Description of the three PhD programs
These are short descriptions of the public policy, statistics, and joint public policy-statistics PhD programs:
- The Heinz public policy program provides students with tools with which to rigorously address fundamental problems in public policy and management. It has very flexible course requirements so students can focus on their specific interests.
- The statistics program provides very rigorous training in fundamental statistics, computation, and machine learning techniques. Students are trained to develop new methodology for specific problems, and they can choose to study theory or applied statistics.
- The joint statistics-public policy program is essentially a combination of the statistics and public policy PhD programs. Students work closely with two advisors, one in the statistics department and one in the public policy school.
Why, you might ask, would anyone want to do a double PhD program?
These are the three main reasons I chose to become a part of the joint program:
- Students are trained to develop new statistical methods as they pertain to a specific social problem, so they are not constrained by the limits of existing methodology.
- Students are trained to communicate complex information and results in a way that is intelligible to other human beings (specifically, policy makers).
- Instead of acting like a statistical consultant that helps someone else analyze data and solve a problem, students can take ownership of projects and ask their own questions.
Of course, this does not mean that if you are only in the statistics PhD program you will never have ownership of a problem, or that if you only do public policy you will not study rigorous statistics methodology. In fact, many students from both departments end up doing research that is very similar to the joint students’. Training in the joint program, however, is more comprehensive and detailed than in each program separately.
What are the requirements for the joint statistics-Heinz program?
Regarding the workload, the combination of the two programs is not exactly the sum of the requirements for each, since the statistics and public policy programs are not mutually exclusive, but it does have about 1.5 times the requirements of a single program (and it takes about the same amount of time as a Heinz doctorate to complete).
- For statistics, the required courses are Intermediate Statistics 36-705, Applied Regression Analysis 36-707, Advanced Probability Overview 36-752, and Advanced Statistics 36-755.
- For Heinz, the required courses are PhD Microeconomics 90-908, Econometric Theory and Methods 90-907, and a social science elective.
In addition, students must write two papers (one of them must be joint statics-public policy, the other is just public policy), and take workshops that help them throughout the process of writing the papers. The papers must be culminate in publishable reports that are presented orally and in writing.
The dissertation is a joint project between the two departments.
What are the TA responsibilities for the joint statistics-Heinz program?
Students in the joint program must TA one semester for Heinz and one semester for statistics each year, except the first. The first year there are no Heinz TA duties.
Do you recommend the joint program?
Absolutely. Carnegie Mellon University encourages interdisciplinary work in all disciplines and is very supportive of joint programs. My favorite part about the stats-Heinz PhD program is working closely with advisors from the statistics department and Heinz College. I enjoy being part of two very different departments and having support from numerous sources.
If you have any questions about the program, do not hesitate to write me an email.