Undergrad Institution: big midwest state school ( ranked <30 on statistics) Major(s): math and stat double GPA: 3.83
Type of Student: international female
Grad Institution: not good private school (ranked 50-70 on stat US News)
Concentration: statistics MS GPA: 4.0
GRE General Test:
Q: 170 V: 151 (52%) W: 3.5 (<50%) GRE Subject Test in Mathematics:
M: took two years ago, did really bad TOEFL Score: N/A
Programs Applying: Statistics and Biostatistics PhD
Research Experience: Summer data analysis in a biology lab, haven't done much, only used basic lm and glm. Another biostat related machine learning summer research in an ivy school, may publish paper, not sure if it can be first author Awards/Honors/Recognitions: 2 years Dean's list for undergrad, tuition fellowship for MS program Pertinent Activities or Jobs: tutored for a year, TAed for a year. Both are for introductory stat undergraduate classes.
Letters of Recommendation: 1 my advisor for my master program, took his class and got an A. 2 chair of the department, took his class and got an A. 3 research supervisor from the ivy school
Math/Statistics Grades: Have taken a good amount of undergraduate math courses, got mostly A's, only 2 B+. Have taken master level probability and statistics (Casella & Berger) (A). Also took some applied statistics courses on both undergrad and grad levels. Any Miscellaneous Points that Might Help: currently in a stat master program, and plan to take two PhD level probability and inference in Fall 2019
I want to apply to biostat phd program in Columbia, UCLA, Penn, Yale, Brown, BU, Duke, UNC and UMN, and stat PhD in UCLA , JHU, NCSU and UC Irvine. But I have no idea if the goal is too high for me? Which should be reasonable schools to apply?
Also, my GRE score is one of my biggest concerns. Should I take GRE again to improve my verbal and writing? I don't know if GRE score is that important...