Stats PhD Evaluation - what range of schools should I apply to?

[confusedbear]

I'm finishing up my junior year as an undergrad and starting to think about what schools I should be applying to if I would like to do a PhD in statistics. I will also be asking my advisor for senior thesis as well once school starts back up again but I'd like to know honestly what you guys think. I'm planning on taking a gap year after undergrad to apply but I do want to start thinking about this now.

Undergrad Institution: Berkeley (domestic)

Undergrad Major: BA in Computer Science and Data Science

GPA (Undergrad): 3.90, overall and major

Relevant Courses: 

Calc 2/3 (A+, B+), Linear Algebra and Differential Equations (A+), Linear Algebra upper div (A), Discrete Math (A), Applied Probability Theory (A), Various algorithms/cs theory courses (all As), Machine Learning (A-), Various computer science courses (all A's), Data Science courses (A+, A-), Statistics (A).

Will take real analysis, numerical analysis, optimization in senior year. (edited after feedback )

Research: 

• I've done some work as an undergrad RA for some grad students here, but no papers or independent work yet
• Will write a senior thesis in applied statistics/data science

I have not taken the GRE yet but have been studying and from my practice exams I'm expecting 165+ quantitative score and 160+ verbal. I have been TA-ing an undergrad math class. During my summers I have been doing software at a big tech company.

I know my profile is not super competitive in terms of research which is the most important, but I'm beginning to realize that that is what I want to do rather than computer science-related things. I'm hoping my thesis will help prove that I like and can do independent research. That being said, knowing I have this weakness in my profile but otherwise good academics, I'd like to know honestly what range of schools I should consider applying to. Thanks! 

Edited May 15, 2020 by confusedbear

[Stat Assistant Professor]

Your profile is actually pretty good. With a 3.9 in a math-y major from UC Berkeley, you should be in really good shape if you take a bit more math. 

I would recommend taking a few more math courses like numerical analysis and optimization, instead of econometrics or more statistics courses. For Statistics PhD programs, mathematical preparation is far more important than having taken a bunch of undergraduate applied stat courses (in fact, a not insignificant number of first-year Statistics PhD students have never taken a probability/statistics course before enrolling).  

Admissions is very competitive at the top Statistics PhD programs, so it would be good to apply to a semi-wide range of schools. But if you do well in real analysis, I could see you getting into a school like TAMU, Purdue, or Penn State (and you could likely get into a higher ranked school as well).

[StatsG0d]

I think you could aim a little higher than what @Stat Postdoc Soon Faculty says. My profile was weaker than yours, and I got into all the schools they mentioned.

[Stat Assistant Professor]

30 minutes ago, StatsG0d said:

I think you could aim a little higher than what @Stat Postdoc Soon Faculty says. My profile was weaker than yours, and I got into all the schools they mentioned.

Absolutely agree. Just to clarify: I think the OP should consider the programs I mentioned as in the "lower end" of the range of schools they should apply to. I believe they can get admitted to a top-tier program like University of Washington.

[confusedbear]

Thank you for the advice and evaluation @Stat Postdoc Soon Faculty and @StatsG0d! I will keep your advice in mind and take the math courses you recommended instead.