WarAndPeace

This is very helpful. I appreciate the insight. I'm not first author, but significantly contributed (e.g. ~2 years of work on the journal, some theory and all implementation on the conference). My letter writers on the research side are well-known and at an IVY institution, but not in the statistics department: 1 in computer science (heavy emphasis on bayesian methods), and 1 who is a pioneer in applied mathematics (MCMC and the likes). I've known/worked with them for about 3 years, so I expect them to be stellar. I gather from your reply that it will be a crapshoot, more or less, for the more difficult schools as this point. Always difficult to accept! Thanks again.

Thank you, I will add some schools in that tier to my list. Do you have any advice on maximizing my chances, or improving my profile? For example More pure math (delay application a year). In the spring I could take some combination: Algebra I, Algebraic Topology, Differential Geometry, Functional Analysis, Harmonic Analysis. Scoring high on math subject test. Theoretical statistics research (hardest to gain out of the 3 though).

Hi Everyone, Any advice on schools to add/remove given my background and research interests? Undergrad Institution: Large Public School, around top 100 (US news) Undergrad Major: BA in Mathematics GPA (Undergrad): 3.72, overall and major Type of Student: Domestic Relevant Courses (Undergraduate): Calc I/II/II (A-, B, A-), Analysis I/II (A-, A), Linear Algebra (A), Discrete Math (B+), Differential Equations (A), Applied Probability Theory (A), Algorithms (B+), Applied Probability Theory (A), Math Stats (B-), Machine Learning (A), Econometrics (A-) Research: 1 semester of math research in number theory, internship in machine learning 1.5 years as a research associate out of undergrad at a top business school (Wharton/Columbia/Stanford). Some applied statistics, nothing real theoretical. _____________________ Graduate Institution: Public School, around top 30 (US News) Major: MS in Mathematics GPA (Graduate): 4.0 Relevant Courses (Graduate): Real Analysis I/II (A, A), Complex Analysis (A), Probability I/II (A, A), General Linear Models (A), Statistical Estimation (A), Multivariate Stats (A), Statistical Learning (A), PDEs I (A), Hypothesis Testing (Fall), Stochastic Calculus I (Fall), Algebra I (Fall) Research: Top Artificial Intelligence conference involving bayesian inference Journal Publication, Finance and Economics Recs: 3 strong letters: 1 from probability grad class, 2 from research GRE General: Q/V/A: 168/163/5 GRE Math Subject: Planned on taking in September, but not sure whether it will be offered in the fall with the COVID19 situation. _____________________ Research Interests: Bayesian inference, High dimensional inference, Graphical models, Stochastic analysis (stochastic differential equations) Prospective Schools: Statistics only, but I am also planing on applying to several Applied Math/CS PhDs which cover the research interests above. US: Berkeley, Duke, NCSU, Columbia, Yale, Michigan, Texas Non-US: Toronto, Oxford