Profile Evaluation for Statistics PhD

[StatPhDHopeful]

I want to pursue a statistics phd, but I am not sure that I have the appropriate background (I am not a math major...). I provide highlights of my profile below.

 

Undergraduate

US University

Engineering Major

GPA: 4.0

Relevant Coursework: Calculus (A), Multivariate Calculus (A), Linear Algebra (A), Discrete Math (A), Engineering Probability (A), Engineering Statistics (A), Engineering Stochastic Models (A), Honors Real Analysis (A), Object Oriented Programming (A)

 

Graduate

Masters Degree (mostly PhD coursework though)

US University

Engineering Major

GPA: 3.9

Relevant Coursework: Two semesters of PhD Engineering Stochastic Models (A and A-)

 

I have coding experience in Java, C#, Matlab and SAS.

 

Research Experience 

Nothing relevant

 

Schools

Duke

Columbia

Cornell

UCLA

Yale

Rice

NYU

Northwestern

 

Do I have a shot at any of those programs? I understand that many of those programs "recommend" the GRE Math subject test. What range of GRE Math scores might help my application for those schools?

 

I am considering taking additional math courses such as graduate linear algebra and a second semester of real analysis. What math courses might a statistics admissions committee like to see? 

 

I have no context whatsoever at the moment, so I appreciate any comments/ advice.

[Bayesic]

I think your background sets you up very well to get into one of those graduate programs.  Even though you didn't major in math or statistics, you still got an excellent grade in Real Analysis, which is the class that admissions committees look for when they are trying to determine whether your math background is suitable for a PhD program.  IMO, a second semester of real analysis would be the most helpful for your application if you were going to take another math course.

 

In my opinion, unless you got a very good score on the GRE math subject test (75-80%+), don't bother submitting your score to schools that merely recommend it.  I think most schools realize that a multiple choice test on subjects ranging from number theory to topology is not the most predictive when it comes to statistics PhD outcomes.  However, it can serve as a proxy for general mathematical knowledge, which is why some schools like to have it.

 

Many of the schools that you listed are relatively small programs, which makes them harder to get into and narrows the range of research topics available in the department.  May I ask why you chose those specific programs?

[StatPhDHopeful]

Bayesic, thanks for your response.

 

I admit to not knowing much about the academic terrain in Statistics. I picked the schools that I listed based primarily on geographic preference. Along those same lines, I would also be interested in programs in the Southern Ontario area (e.g. Queens, U Toronto, U Waterloo, UWO). 

 

Are there any resources that provide a good overview of Statistics departments from the perspective of a prospective PhD student?

[wine in coffee cups]

Geographic preferences are a fair starting point, though you've omitted a number of programs that logically should be there based on the regions you included (e.g. UNC, Chicago). I would prioritize them based on your research interests, which you didn't mention, but you must have some stuff in mind if you're coming from engineering and making a switch now. There's not like a central site that lays it all out for you unfortunately, you have to figure this out by talking to statistics faculty and looking at department webpages and lists of publications. As Bayesic said, some of the programs you listed are quite small and idiosyncratic in their admissions (Yale, Northwestern, NYU Stern), so I'd only apply to those if there actually is somebody there you'd want to work with. Add some bigger departments to your list like NC State or Michigan.

[StatsG0d]

I think you've got a pretty great shot at almost anywhere. wine in coffee cups said it best about the idiosyncratic programs. I've been subject to their idiosyncrasies myself. I would definitely at U Chicago onto the list and maybe Purdue, who places a heavy emphasis on computation (which I assume you're interested in due to your engineering/computer science background.