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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 for fall 2020. I posted my profile recently and got great feedback, and I was wondering about a few more things:

1. I changed the list of schools I'm applying to, do they seem reasonable? I wanted to apply to more reach schools to give myself a better chance of getting into one, while also applying to enough lower ranked schools to not feel worried about getting into zero schools.

2. If I'm okay with doing a master's instead of a phd(in preparation for a phd), in general will it hurt me to apply for the phd programs? I.e. are there schools where you would get rejected outright(not even offered a master's) if you applied for the phd program but where you be accepted had you only applied for the master's?

Undergrad Institution: Large public university ranked top 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: (probably won't take)
Programs Applying: Statistics PhD/M.S
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 I think the stats prof 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.



Calc III(took in hs and it stayed on my transcript :///) (B), Linear Algebra and Differential Equations(honors and proof based) (A), Multi-Variable Calculus(honors and proof based) (A), "Applied Mathematical Analysis" which was a mixture of harder calc III and some complex analysis(honors) (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), Intro. to Combinatorics (A)


Computer Science:

Intro. to programming (A), Data structures (A)



3 intro classes (A,A,A) a lab course (A), quantum mechanics (A), thermodynamics (A), classical mechanics (A), electrodynamics (A)


Additional courses I will have taken before applying:

Numerical Analysis, Stochastic Processes


Schools I'm thinking about applying to:(For statistics phd unless otherwise indicated)

"Safety"(not really of course):

Iowa State, Madison, Illinois UC, Purdue, John Hopkins(applied math/statistics)



Chicago, Columbia, U Washington, CMU, U Penn


Any suggestions/feedback would be great! Thanks

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Looks reasonable to me. I'd be pretty surprised if you didn't get into Iowa State, Purdue and Illinois, but they are good schools so I wouldn't say you have any true safeties on your list.

Most programs will have an option asking if you'd like to be considered for their master's if you aren't accepted to the PhD and you can simply check that box. I don't see a master's degree helping your profile much and wouldn't recommend it unless you are independently wealthy. Since a MS takes two years and the PhD program that accepts you will at most only transfer one year of those courses, you are equally well off just reapplying if you aren't happy with your results. 

Instead of worrying about masters programs, I'd add another couple big programs in the match range (think OSU, TAMU, PSU) and a few lower ranked schools or biostat programs.

Edited by bayessays
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