superk60

Thanks Bayesian, this is very helpful. Let me add that I had a rough freshman year (health issues), so my ex-freshman GPA rounds to 3.6. No idea how I'll address that on the application (!). I'm also taking an grad course in the fall with one of my potential recommenders, which might help a bit. To give you an idea of risk tolerance, I'm targeting Pr(getting into >= k schools) = 1-0.15*k for k ∈ {1,..,5}. Given what you said, here are some more UConn/less Yale schools: UCSB University of PIttsburgh Boston U Rutgers UC Irvine Colorado State So my list might be... Reach/Group 1: UT, Yale, Michigan, UCLA Group 2: UConn, Boston U, Rutgers, Rice Group 3: Colorado State, UC Irvine, UCSB Reasonable? Also, if I were to put in for biostat (at schools that have it), would that help?

Hi guys, I am looking at programs for the Fall 2019 admissions cycle (stats Ph.D): Undergrad Institution: Top 25 Private (top 10 for stats) Major(s): Mathematics GPA: 3.3 (3.4 expected) Type of Student: Domestic Asian Male GRE General Test: Taking soon. Will probably take math GRE too. Programs Applying: PhD in Statistics Research Experience: Will be doing independent study/research in the fall on numerical linear algebra. Worked on applied stats research project with professor. Did quant research at a hedge fund last summer. Letters of Recommendation: One from research advisor, one from real analysis instructor (very strong up-trend in performance), one from independent study advisor. Relevant Course Work: Math and Stat Courses: 4 stats courses: A's, Linear Algebra: B, Real Analysis 1/2: C/A, Probability: B, Numerical Analysis: A, Computational Bio: A Computing Skills: Python (software engineering experience), R, Matlab Applying to: Statistics Penn State USC UConn Yale Michigan Ohio State UCLA Rice Brown UT Austin Probably way too ambitious, feel free to recommend some substitutions/deletions Thanks in advance.