stats_phd_hopeful

Hello, I applied to a number of highly selective stats PhDs last year and wasn't admitted to any of them. Over the past year, I have filled in some missing coursework (e.g. I took real analysis), and I've been working on a research project with a well known professor who is writing me a letter of rec. I'm applying again to these schools this application cycle. Will my new application actually be reviewed? I'm worried that some schools might have an automated system where if someone has applied before they just get dumped in some separate pile and never get looked at. Thanks!

I know it's a little late at this point as I've already applied, but I'm curious as to what other people think my chances are given my profile: Undergrad: Top 5 overall US News / Top 5 Statistics Programs US news, not known for grade inflation (if anything deflation) Major: Statistics GPA: 3.8 Masters: Same as Undergrad, all done in 4 years. Major: Statistics GPA: 3.8 Courses: Math: Calc III (A), Multivariate calculus (A-), Differential Equations & Complex Variables (B), Optimization (Graduate) (B), Linear Algebra (A), Linear Algebra (Graduate) (B+) CS: Honors Intro to CS I (A), Honors Intro to CS II (A), Data Engineering (A), Computer Systems (A-) Stat: Probability (A-), Stat Theory I (A), Stat Theory II (A), Applied Regression (A), Machine Learning (Graduate level) (A), Causal Inference (Graduate Level) (A), Stochastic Processes (A), High Dimensional Data (A), Regression Analysis (Graduate) (B+), Nonparametric Statistics (Graduate) (B+), Generalized Linear Models (Graduate) (A-), Time Series Analysis (Graduate) (A), Statistics Genetics (Graduate) (A), Bayesian Nonparametrics (Graduate) (A), Modern Applied Statistics (Graduate) (A). Research Experience: Master's thesis in my fourth year of school. Theoretical stats paper with applications to genetics with accompanying R package for methods. Paper on arXiv, R package on CRAN. Work Experience: 1 Year at sports team doing analytics. 2 Years at hedge fund writing code for systematic strategy. LORs: (1) Well known professor of Statistics with tenure. Was my Master's thesis advisor. Extremely strong. (2) Former boss at my first job that heavily used statistics. They have a PhD in stats from a top 3 institution. Should be relatively strong (3) Professor from stochastic processes class. Not well known. Not very detailed and I think will be fine. Research Interests: Bayesian statistics, statistical genetics. Places Applied: Stat PhD: Stanford, Berkeley, UWashington, UPenn, Columbia, UChicago, Harvard Biostatistics PhD: UWashington, Harvard, JHU, UCLA Strengths of Application: Did undergrad and Master's in Statistics in only 4 years. Earned good grades in some very hard PhD level statistics courses. Interesting industry experience. My first letter will be extremely strong. Weaknesses: Not the highest GPA. No real analysis (I'm especially concerned with this). The reason I didn't take analysis is that I was so focused on getting as much applied statistics knowledge as I could and I really didn't know how important analysis was to the PhD apps process. Overall, I think I have a decent application but a few big holes (mostly no analysis). I'm hoping that good letters and enough strong applied statistics experience may be able to make up for this. I also know that I'm applying to an incredibly selective list. I certainly would have been open to applying to more schools but unfortunately I'm quite picky about location. If I don't get in anywhere this cycle my plan is to quit my job, take analysis over the summer at an Ivy near me, do some more research, and do the process all over again. I know that most schools really want analysis but I'm hoping that I've demonstrated my strengths elsewhere and that schools would be willing to let me take analysis when I start the program.