What courses do I need to prepare for a PhD in Political Science?

by Justin Esarey

[This article was first posted on October 13, 2013 at The Political Methodologist.]

I recently had a discussion with some of my graduate students about what an ideal preparation for a PhD program in Political Science would look like. They were discussing the issue because they felt that very little of their undergraduate Political Science education prepared them for what they’d be learning in graduate school, especially in terms of methodological tools and design approaches to applied research. I felt it might be valuable for undergraduates thinking of pursuing the PhD–or new graduate students who hadn’t realized what they were getting themselves into–to post the question to the community at large and have the responses on TPM as a resources.

When undergraduates ask me this question, I usually tell them that someone hoping to study a substantive area (International Relations, Comparative Politics, American Politics, or Policy) would ideally have taken:

  • two semesters of calculus, including differentiation, integration, and infinite series;
  • one semester of matrix linear algebra;
  • one semester of (a) undergraduate econometrics or (b) probability theory from a statistics department;
  • one semester of programming in a relevant language, such as Python, MATLAB, or R;
  • some kind of serious research design/epistemology class; and
  • as many courses as you can take that include reading published academic literature in your subject area (look to see that the syllabus assigns academic journals or university press books, not textbooks)

Some courses may kill two birds with one stone if, for example, they use MATLAB or R as a part of teaching some other subject.

Those hoping to work in methods or formal theory should consider pursuing a Math minor or double major, including all of the above courses plus:

  • a semester of three-dimensional calculus;
  • a semester of real analysis;
  • a semester of differential equations;
  • a semester of discrete math;
  • a semester of some form of mathematical microeconomics class at the advanced undergraduate or introductory graduate level;
  • as many econometrics or applied statistics courses as you can fit into your schedule on top of the above.

Designing an appropriate preparation for people who plan on being area specialists and spending a lot of time in the field using qualitative methods is somewhat outside of my area of special expertise. With that proviso, I usually recommend the following courses in place of the lists above:

  • at least one semester of calculus, covering differentiation and integration;
  • one semester of matrix linear algebra;
  • fluency in at least one of the following: Spanish, Chinese, Russian, Arabic (chosen to best-suit your area of interest)
  • reading and writing proficiency in another language relevant to your area
  • as many courses as you can take that include reading published academic literature in your subject area (look to see that the syllabus assigns academic journals or university press books, not textbooks)

This list replaces most of the math with language training.

It is, of course, worth noting that very few students–including those who are very successful–come into a PhD with this amount of training. But my own undergraduate adviser told me that the more of this stuff that I could get out of the way before I got to graduate school, the more that I could focus on learning the substance of the field rather than picking up mathematical tools. I think that was basically good advice.

What courses would you add to or subtract from this list?

[Update, 10/15/2013 @ 1:07 pm]: Added some language to the qualitative preparation list to clarify that this is in place of the other lists.