mahof

@icantdoalgebra thanks for the advice! What's 210B and why would it be useful for me? I took a quick glance at the prereqs and apparently it needs 205B too. The reason I was thinking of doing 205AB instead is because it is more directly aligned with my interests in population genetics.

@insert_name_here, @bayessays, @DanielWarlock. Thanks for the feedback everyone! So you don't think that taking Abstract Linear Algebra + Mathematical Optimization Pass/No Pass this semester because of COVID-19 will hurt me? Or my lack of dedicated programming classes in college? Those are two things that have been worrying me a lot. Phew, it's reassuring to hear that you guys think I'd be competitive for a top PhD program as my profile stands right now. I guess there are two reasons I'm a bit hesitant to apply for a PhD right now. The first is that even though I enjoy my research a lot, I'm not sure if I'm cut out for the rigors of a PhD and if I'd even want to be in school for 5-6 more years. Thus, my thinking is that a masters will help me figure out if I want to continue on with grad school. The second reason is that I might choose to apply to some top CS PhD programs like Berkeley, Stanford, MIT, Princeton, etc. because these departments do a lot of research work in my areas of interest too. I've read online that the competition to get into these programs is super intense and having publications before applying can be very helpful for CS PhDs. So my thinking is that if I do a MS before my PhD applications, I have more time to publish and strength my app that way. What do you think? Thanks so much in advance!

Hey everyone! I wanted to get a better sense of what my chances are for an MS in statistics at some top programs. I intend to use my MS experience to improve my profile for a Statistics or CS PhD and to also figure out if I want to go down the PhD route or not. My area of focus in undergrad research has been statistical genetics and biostatistics/computational biology type stuff and I'd like to continue this in grad school. One caveat is that I'm currently a junior so I won't have my senior year grades when I apply in the fall. So my profile below is based on everything I've done so far. Undergrad Institution: Berkeley Undergrad Major: Bachelor of Arts in Mathematics and Statistics GPA (Undergrad): 3.84 Overall GPA, 3.85 major GPA Type of Student: Domestic Relevant Courses(Undergraduate): Freshman Year: Calculus II (B), Introduction to Programming (B+), Multivariable Calculus (A), Linear Algebra and Differential Equations (A-), Foundations of Data Science (A-) Sophomore Year: Probability Theory (A), Real Analysis (A), Complex Analysis (A), Statistics (A), Abstract Algebra (A), Junior Year: Analysis II (A), Abstract Linear Algebra (Pass), Mathematical Optimization (Pass), Introduction to Functional Analysis (A), Partial Differential Equations (Taking this summer) Senior Year: Statistics Honors Thesis (A), Math Honors Thesis (A) Relevant Courses(Graduate): Junior Year: Statistical Genetics (A), Mathematical Population Genetics (A) Senior Year: Measure-Theoretic Probability Sequence (Stat 205A+Stat 205B), Applied Statistics PhD Sequence (Stat 215A+Stat 215B), Algebraic Topology, Differential Manifolds Relevant Research: Research under one EECS and one EECS/Stats professor. I've been conducting research into developing visualization and statistical methods for high-throughput genetic data and also in mathematical population genetics (things like allele dispersion). I might have a publication by the time I apply, working hard on that paper this summer. I've also written honors thesis for the statistics major and math major. The stats thesis focuses on statistical methods for genetics and the math one is on stochastic analysis in population genetics. Recs: 2 very strong letters of rec from my research advisors. A third regular one from my Real Analysis professor. GRE General: V/Q/A: 167/168/5 Relevant Work Experience: I spent my freshman summer interning as a software engineer at a startup. I spent my sophomore summer as a software engineering intern at Google. Programs Applying: Stanford MS in Statistics, UChicago MS in Statistics, Oxford MSc in Statistical Sciences, Cambridge MASt in Mathematical Statistics Current status: Wrapping up my junior year and doing research this summer I have 3 main concerns I was hoping to hear perspectives on- 1. I took Abstract Linear Algebra and Optimization Theory for a Pass grade (not letter grade) this semester because of COVID-19. The math department sent out a mail advising everyone to take all classes Pass/No Pass so that's exactly what I did. I've heard Abstract Linear Algebra is incredibly important for Stats grad school, and I only got an A- in lower div Linear Algebra+Diff Eq's. How much will this hurt me? 2. I have a lack of programming classes, and in the only programming class I took at Berkeley, I received a B+ (my studying habits were nonexistent freshman year). However, I've been programming for several years now and I have two software engineering internships (one at Google) to back this up. Will I be ok in this regard? 3. I've heard publications are really important for grad school. I have strong research experience, but I'm not sure if my paper will be published by the time I apply. Will this be held against me for these top programs? So that's my entire profile. I was hoping to gauge my chances for the programs I'm applying to and if there's anything I can do to improve my chances before I apply this fall. Like I said, I want to use this MS to improve my CS/Statistics PhD profile and to also figure out if grad school is for me. I'd also to love to hear if there are any other programs I should apply to. Thanks so much!