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Fall 2020 Statistics PhD Application Evaluation

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Hi all,

I'm a senior undergrad in the US graduating in the spring. I'm applying to PhD programs in statistics/biostatistics for fall 2020. I'm wondering about several things:

1. Are programs in biostats vs statistics significantly different? I think I'm interested in a more theoretical/mathematical training so if biostatistics programs put a lot less emphasis on that then I'm not sure I'd want to attend those programs.

2. Are the schools I'm applying for reasonable? Suggestions on where else to apply would also be great.

3. Will not taking the math GRE subject test significantly weaken my application to higher ranked schools? I'm not sure if putting in the time to prepare and take it is worth it; I was planning on taking a practice test and seeing how that goes.

4. Should I retake the general GRE? I think I could get at least a 4.5 writing score and a higher quantitative score with not that much more preparation.

 

 
Undergrad Institution: Large public university ranked 15-20 in math by US news

Major(s): Applied Mathematics
GPA: 3.89

GRE General Test:
Q: 166 (89%)
V: 165 (96%)
W: 4.0 (57%)
 
Math Subject Test: (not sure if I will take)
Programs Applying: Biostatistics or Statistics PhD
Research Experience: Did a project related to Dynamical Systems with an applied math professor, and this summer have been doing a project with a statistics professor that I'll continue into the fall semester.
 
Letters of Recommendation: Two from the professors I did projects with. The applied math professor will probably write an at least ok letter and the statistics prof I think will be able to write a strong one. I'm going to ask a physics prof I took quantum mechanics with for the last letter because I did very well and I thought he liked me. In general I didn't form that close of relationships with my professors so I'm sort of worried about this last letter but I have several professors I took classes with as backups.

Grades:

Mathematics:

Calc III: B

Linear Algebra and Differential Equations(proof based): A

Multi-Variable Calculus(proof based): A

"Applied Mathematical Analysis" which was a mixture of harder calc III and some complex analysis: A

Intro. to PDEs: B

Analysis I, II: A, A

Intro. to Measure Theory and Integration: A-

Intro. to Probability Theory(proof based): B

Modern Algebra I, II: A, A

Numerical Linear Algebra: B+

Intro. to Mathematical Optimization: A

 

Computer Science:

Intro. to programming: A

Data structures: A

Intro. to Combinatorics: A

 

Physics:

I took 3 intro classes, a lab course, quantum mechanics, thermodynamics, classical mechanics and electrodynamics and got all As. Initially I thought I wanted to do a physics PhD which is why I took so many physics courses and not so many statistics courses.

 

Additional courses I will have taken before applying:

Numerical Analysis

Stochastic Processes

 

Schools I'm thinking about applying to(and US news ranking):

John Hopkins biostats 3

University of Chicago stats 6

University of Michigan Ann Arbor 12

Duke stats 12

Columbia stats 16

University of Wisconsin Madison stats 16

Iowa State University stats 20

Minnesota twin cities stats 24

Ohio State University 37

University of Illinois Urbana-Champaign stats 37

 

Any suggestions/feedback would be great! Thanks

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Working backwards, to answer 3 and 4 quickly, I don't think you should retake the GRE and I don't think it's worth taking the math subject test - I don't see you getting into the schools that require it.

On question 2, I think the first few schools are unlikely (especially Chicago) and that the Madison-UIUC part of your list should be your targets.

On 1, if you could get into a top 5 biostat program, there will be opportunities to do theoretical research.  However, your classmates will likely be very interested in applied research and you will be in a public health school surrounded by that. If you really just want to think about math, I think it makes sense to go to a statistics program if you want classmates that share your passion. 

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You're applying to a slate of schools that seems pretty similar to what I applied to, and I think your profile is stronger than mine, which would suggest that you should probably be able to apply to these schools with a good expectation of some choice (although, as a warning, I do feel like a lot of applicants on here are stronger than I was).  Maybe you could aim for a slightly more top-heavy approach to provide more high-tier choices, or at least consider applying to a couple high-ish places in addition to what you already listed above.  Bayessays knows more than I do, so I don't intend to disagree particularly, but I think you'd have a decent chance at Duke at least -- since they're pretty exclusively Bayesian, they use a lot of MCMC, and I think that might predispose them to liking people with physics/physics simulation backgrounds.  

To echo bayessays, the higher ranked biostat departments will have the theoretical background you're looking for.  I've usual heard that two of the top biostat programs require measure theory -- Washington (Seattle) and UNC -- so those might be ones to consider as well.  That said, they would probably all let you take those more theoretical courses if you wanted, so that shouldn't be a reason to remove Johns Hopkins or anything.  

 

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Yes, I didn't mean to sound so heavy-handed. It's hard to give detailed advice on every single choice when the list is not in the order of difficulty. I don't think OP will get into Chicago or Columbia, but I could see them getting into Duke or Michigan or even JHU.  I just think they should mainly be targeting those other schools and consider schools like Duke to be on the reach end.

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I think your profile is pretty good, and that you'll get into several of the lower ranked schools on the list you produced - i.e. if you're satisfied with going to one of those places then you can relax.  My advice is to apply to your dream schools even if you think you don't have a shot because you might regret not doing that if you get into most of the places you applied.  Also, I think USnews' grad schools ranking is very poor because their methodology is purely based on an opinion survey of faculty members and doesn't directly account for actual research done by a department.  It's more important, in my opinion, what faculty in a department actually produces in terms of research, and this will govern reputation in the long run regardless.  Look through faculty at the schools you wanna apply at to actually get an idea of who you might want to work with, gear your SOP at each school toward those areas, and hope for the best

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