I'm about to start my junior year and would like to gain some insight into how I can be a more competitive applicant for statistics and biostatistics PhD programs during my final two years of college. I plan on applying for Fall 2022 but am considering taking a gap year to gain more research experience.
My profile:
Undergrad: Top 150 large state school
Major: Mathematics
GPA: 3.96
GRE: aiming for 167 for quant and 162 for verbal
Type of Student: Domestic Asian Female (US)
Math Classes: Calc I (A+), Calc II (A), Calc III (A), Linear Algebra (A), Differential Equations (A), Intro to Proofs (A), Intro to Statistical Computing (A+)
Research: 1 year of experience in a biochemistry lab, no publications. Currently cold-emailing professors doing statistics research and hoping to start sometime this upcoming semester. I also plan on applying to stat/biostat REUs for summer 2021.
Activities/Jobs: TA for multivariable calculus. Looking for fall and spring internships in data analysis/data science.
Tentative Schools
UC Berkeley - Stat PhD
UCLA - Stat PhD
Columbia - Stat PhD
Carnegie Mellon - Stat PhD
UPenn - Stat PhD
Texas A&M - Stat PhD
UT Austin - Stat PhD
Rice - Stat PhD
UCSB - Stat PhD
UCI - Stat PhD
University of Washington - Biostat PhD
Emory - Biostat PhD
Harvard - Biostat PhD
JHU - Biostat PhD
Most of these schools are reaches and very competitive, but these are a general idea of where I'd like to attend.
Questions
I've switched majors a few times and recently decided on going to grad school, which is part of the reason why I don't have any relevant research experience. Will this hold me back significantly?
Would it be better to take a gap year (doing research or working in industry) or apply for masters programs to strengthen my PhD application?
I come from an unknown undergrad. How will this affect my chances for a top 20 program? What can I do to strengthen my application?
How important is undergraduate publishing for PhD applications?
Thank you for reading through! Any advice would be appreciated!