randomwalker

I'd just take the letter grade. Some professors I've spoken to say that adcoms may assume the worst (B- or C) when you p/f a class, and real analysis is arguably the most important class on your transcript. As to how much it will hurt? Probably contingent on your performance in other math classes and the rest of your profile. For reference, I got a B+ in RA with mediocre grades in some of my other math classes and was still fortunate enough to get into some T30 programs.

Also received one. I appreciate how well-thought out it was but it seems a bit atypical for programs to do this.

Also received an acceptance this morning from UC Irvine after an interview on 1/23. I was told they are aiming for a cohort size of 10-12, so maybe other rounds are coming later? It seems like their yield is about 30-40% so one might expect them to admit around 30 students.

Hi everybody, I would appreciate some insight as to whether or not I am being realistic about my current list as well as some suggestions for additional schools that might be a good fit. I'm primarily interested in Applied Statistics with applications to the social sciences but not necessarily from an economic perspective (thus why I'm not applying to proper economics PhD programs but may pending the results of this app season), possibly causal inference or Bayesian flavored. Undergraduate Institution: T5 Major: Math and Statistics, Economics GPA: 3.75 Background: Domestic White Male Related Coursework: Undergraduate Level: Intro Stats (A), Proof-Based MV Calc and Linear Algebra (B-), Data Structures in Java (A-), Econometrics (A-) Masters Level: Linear Regression (A), Statistical Computing (A), Elementary Stochastic Processes (B-), Machine Learning (A), Bayesian Statistics (A), Real Analysis I and II (B+), Statistical Inference (A), Probability Theory (A) PhD Level: Statistical Inference (due to take in the Fall) Research: -Did an REU on spectral clustering and randomization techniques for directed graphs, presented to school undergraduate research conference -REU led to a paper on differential privacy in graphs that is likely going to be submitted sometime this Fall -Worked as a research assistant in economics department performing quantile and logistic regressions on outcomes in the labor force -Tried to co-author a paper in health economics with the PhD student I RAed for that had data and funding issues and ended up falling through Work Experience: -Worked as a grader for intro to stats (x3) -Worked in the statistics helproom for undergrad and masters students -Was a peer coach for a statistical inference and surveys class helping with R questions -Was a TA in the Economics Department for a relatively well-known macroeconomist -Data analytics summer internship for large bank Letters of Rec: -Professor who supervised my REU and who I am working with on the upcoming paper -Professor who taught my machine learning class and runs the statistics helproom -Not sure who the third will be, maybe a professor I was a grader for? Extracurriculars: -Was a senior editor for two academic journals, one in social science research and one in economics School List (all PhD): Reach: Duke (dream school), Carnegie Mellon (Stat and Public Policy, also a dream school), UNC, UCLA, UW, UChicago Booth (Econometrics), Columbia, UT Austin Match: UC Irvine, Johns Hopkins (Applied Math and Stat), GW, UVA, Northwestern, Boston