[Profile Evaluation for stats phd]

Undergrad Institution: Top 20 US Liberal Arts College
Major(s): Mathematics
GPA: 3.6 (grade deflation in my department, but still not very competitive I guess)

Type of Student: International Asian Female
GRE General Test: (took July 2017)
Q: 170 
V: 160 
W: 4.0 

GRE Math Sub: Took in October, hope it was a 75th percentile

Programs Applying: Statistics PhD

 

Research Experience: 

• Two summer research in abstract algebra, but the topic was fundamentally statistics related (experimental design direction), one paper under review
• TA for stats course for 3 years, R tutor for one semester

Awards/Honors/Recognitions: One honorable mention in a stats modeling competition
 

Courses: 

• stats modeling and math modeling (both A-)
• higher level math courses like Abstract Algebra and Analysis (did do well in analysis, the worst grade among my math course)
• Probability (A-)
• In data science course right now, and will taking a Bayesian seminar next semester as well as an advanced data science course
• Computer language: C, Java, Scheme, Latex, Mathematica, Matlab, R

Recommendation Letter: One from the professor I did two research with, one from my academic advisor who is a stats professor, and still considering the third one.

Programs Considering (PhD):

• Harvard 
• UC Berkeley
• UCLA
• Johns Hopkings University
• Carnegie Mellon University
• U Chicago
• NYU
• Columbia 
• Washington Seattle
• Duke
• UNC
• U penn
• UCD

 

I wonder am I likely to get into these programs?

Since I did research only in pure math, should I aiming for a more theoretical program instead of an applied one?

Who should I ask for another recommendation letter? 

Thanks for your advice!!