RWBG

They used to have a message on their website that explicitly stated that they did not fund international students. I know, because I would have applied otherwise. It's hard for me to believe they would have left that statement up if that weren't true.

It's not so bad

Pretty sure they've switched to notifying people electronically now, although they also mail a copy of the acceptance, if I'm remembering correctly.

I suspect this is more of an issue with your program, as students who select in are likely to have thoughts about these things that persuaded them to choose your program over others. I think it's more common for those in other programs to come in with no notions on statistics and theory, preconceived or otherwise.

Well this definitely isn't true. I think if you've already applied (so there isn't a signalling component) and you're just trying to learn some things to help you engage with you Ph.D coursework, then proof-writing isn't too bad an option. More generally, while I wouldn't disagree with IRToni that applied statistics may be more helpful to your research than proof-writing, when assessing opportunity costs, you should keep in mind that it is very likely that your Ph.D program will spend time teaching you statistical modelling in a way that they may not spend time teaching you proof-writing, or, say, linear algebra. So, optimizing over the longer term, you may be best served by covering content that will help you engage with the coursework in your Ph.D program better, but will not be covered directly in that coursework. If you have one extra course to take before starting at Ph.D, my recommendation would probably be something closer to pure-math, like taking the calculus course you mentioned, a linear algebra course, maybe probability theory, etc. Though this may not directly relate to the OP's situation, I'd say my advice shifts a little bit if you're thinking about this earlier and creating a plan of courses to optimally prepare you for starting a Ph.D. In this case, I think an ideal set of courses contains both more theoretical courses (e.g. pure math stuff) and more applied courses that can give you a better sense of how you'll use math in your research/can let you get started with research earlier. When I think of some of the best prepared (at least when it came to technical types) students to enter our program in the last couple of years, they tended to have done enough applied stuff to have a research agenda, but enough theoretical stuff to provide them with the "mathematical sophistication" Coach talked about. In my experience TAing one of the statistics courses in our sequence, I found that theoretical courses and general ability to math (yes, I'm using it as a verb now) were far better correlated with high performance in the class than was prior experience with applied statistics coursework (which, informally, seemed almost entirely uncorrelated with performance).

If you haven't already, pick up a proof-writing book like Velleman's How to Prove It. I would posit that proof-writing is the best recreation/relaxation math.

As you suggest, every signal we have is noisy. So the best we can do is consider what kind of applicant a student is, and assign the most appropriate weightings to each signal conditional on that. This may entail putting a high weighting on the GRE Q score for a methodology applicant, and a low weighting on it for a theory applicant. This creates greater ex ante uncertainty about your likelihood of being admitted, but probably results in better ex post outcomes.

The implicit question here is whether we use GRE or GPA scores to whittle things down to a manageable number. We do not; a holistic review of each application is used from the very beginning. I don't feel it's my place to go much further in discussing the details than that, but as a general thing, I think people going into the admissions process are under the impression that there's a greater degree of regularity to this process than there appears to be. Committee members often have a lot of discretion to evaluate applications whichever way they want, which can vary substantially from committee member to committee member.

Perhaps my comment sounded more negative about the process than I intended! Grad students are volunteers, and unlike with faculty, the work does not count towards some service requirement that's ostensibly part of the job. However, it's a fascinating process, and my impression is that grad students do less work than the faculty members. Indeed, there is generally a surplus of volunteers for committee spots. It's hard to volunteer for a position and then complain about getting it.

They do not.

Because faculty are looking to reduce the amount of work they have to do. I take it you object? Admissions: I don't think you have the information necessary at this point to construct a reasonable estimate of your probability of admissions at any particular school. If you could, and we could agree that this probability is conditionally independent between schools (conditional on the quality of your application) and equal at each school, then you could compute things straightforwardly as 1 - (1-p)^n, where n is the number of schools you apply to, and p is the probability of admisisons at any one school. You can obviously do some updating once you start getting offers.

The only insight I have, besides the fact that it almost certainly won't matter that much, is that if it does matter it will probably matter because you've made a very compelling argument that your personal history/diversity is a positive attribute of your profile. I can't imagine an uninspiring statement will count against you, per se, but maybe you can get extra points with your story. But as with all things in this process, it's idiosyncratic, and who knows, you might get a committee member who care a lot about the personal statement. However, I doubt it. Oh, and all your important academic-y stuff should be in the main statement!

I think Irfan was pretty clear about what school the mafia was actually associated with.

Definitely a non-zero (and positive!) number of people who combine formal theory and behavioural stuff, though it's still not a large set. The people doing that kind of thing in political science proper is even smaller, though that might just mean that there's a lot of room to make useful contributions. Who are the Princeton people doing behavioral game theory? Just curious. At Michigan, beyond Skip Lupia, Scott Page has done some behavioral stuff and knows network theory thoroughly (one of his dissertation committee members was Matt Jackson), and Bob Axelrod has done some stuff on this kind of thing in the past, and it's most of what he's interested in right now. You could probably construct a good committee with them and then someone a touch more substantive (maybe Jim Morrow depending on exactly what you mean by electoral violence). If you really want to engage primarily with political science you probably couldn't do better; places like Caltech and Stanford GSB might better prepare you to go on the econ or business school markets.

The set of people studying electoral violence, etc. using behavioral game theory may be close to the nullset. I'm kind of curious about who you're thinking of working with. As to the question of American versus Comparative, it might be worthwhile to look at prelim/field requirements to see which field you would be most likely to fulfill the requirements for. I have one friend who studys Europe mostly, but is being trained as an Americanist because the courses listed under American are the kinds of things that he wants to do, except with Europe. However, as a general point, formal models of elections and electoral violence are fairly prominent in comparative politics, so my guess from your description is that comparative is the better fit.

Thank goodness all the comments I make on my own drafts are things like "good point", "fantastic", and "magnificent job".

I am also wondering this. I know one person who chose not to go to a Top 5 with a publication in political analysis, but they certainly got in. I'd have to say a solo-authored publication in political analysis is a pretty damn good signal, but this is very, very rarely the kind of publication that incoming grad students have.

So, it's probably a good idea to talk a little bit about people at the department to show you've thought seriously about your application and what departments would support you well in pursuing your research. However, ultimately the assessment of fit comes from the admissions committee reading your application and deciding themselves whether or not your proposed work fits with the department. Some professor-based tailoring is fine, but it's possible to overthink the details. My department constructs a list of suggested contacts for each admitted student when setting up meetings for the visit weekend, and these lists tend to be only loosely correlated with the people the students mention in their statement. It's sort of this: show them that you fit by describing a compelling research agenda that suggests a promising scholar that would benefit from the training at the program in question - don't tell them that you fit by quoting some projects that you know some of the adcom professors have written. Also, given space constraints, you want your statement to be talking about other peoples' projects/ideas only as much as is necessary to convey something interesting about you.

Not generally. At least not before decisions are made. Don't worry about relating your work to professors projects: the committee wants to see that you can construct a compelling research agenda, and will draw their own inferences about how you fit with the department.

^Nice.

Apropos of nothing, there's an interesting discussion to be had on how being at whatever department you choose shapes your conception of the field. In my own experience, I've found it really easy to think of the range of things we do as largely representative of the field, and to think of the epistemological approach that dominates here as the approach of the field. However, then I hear from people at other programs, and I'm reminded of how different experiences in political science graduate programs can be, and how "methodological diversity" here means something entirely different than it would at another department.

Well, some places are as methodologically diverse as claimed by making no claims whatsoever to be methodologically diverse. Also, do you have the code for getting R to generate a meal?

I'd say specific area interests are more common on the comp. politics side of the divide, so it might be in your interest to do a CP/IR combination and emphasize the CP. Beyond that, I'd work on developing a narrower research agenda that you can write up for the statement of purpose; noting you want to look at geopolitics, political economy, culture, etc. is fine, but it doesn't indicate to me what within all that you think are interesting research questions.

This reminds me: I need to write up a new quiz for students to get more practice with partial derivatives.

I'd agree that this seems like a natural one to pin. That's up to the moderators though!