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Hi all, as deadlines are approaching, I am doing this last minute chance me/asking for advice post to see if there's anything I missed. Any feedback is welcomed! Type of Student: International student Undergrad Institution and Courses: UCLA stats major, mathematics minor, cumulative GPA 3.85, major GPA 3.72. My grades suffered in freshman year because I was home-sick and I was also juggling a part-time lab assistant job. That said I got a C+, 2 Bs in a lower division math classes. But ever since my second year I have gotten straight As in all my classes. Relevant courses: machine learning, optimization, network theory, numerical methods, real analysis, linear algebra, statistical methods, Intro to Programming. Test Scores: Q169/V164/AWA 4.5, TOEFL 30/30/30/27 LOR: one from an assistant professor at anther prestigious institution who taught me while she was a post-doc at my university one from a very well respected continuing lecturer from my home institution one great one from my last internship mentor. Work/Research Experience: freshman year: Part time at a physical science lab as a lab assistant, did mostly very busy lab work (literally cleaning dishes and data entry) but got exposed to linear regression short internship at an e-commerce company in my home country, worked on business analytics and practiced SQL and A/B testing sophomore year: Worked with a UCLA PhD to quantify social interactions (her paper is now published, but since I only did data cleaning and data analysis work so no title for me) local start-up as a research assistant (doing meta-analysis on Covid related papers) and also did some business analytics work where I analyzed user responses and evaluated the performance of new features junior year: Head project manager at a UCLA data science club Interned at a top US health firm, worked on their fraud detection algorithm (ML stuff like SVM), built data pipelines, data cleaning Current Programs List: NYU MSDS Columbia MSDS Cornell MPS DS track CMU MISM BIDA CMU MCDS Harvard Health DS Harvard DS Stanford MS Stats, DS track UW MSDS JHU DS UC Berkeley Master of Analytics Duke MIDS I am not sure if I am overreaching here. I have talked to few people before and they seem to think this list is more or less reasonable, but I am not that sure myself. I know prestige schools are Harvard and Stanford are definitely hard to get into, but I was hoping I could at least land one school from the list. Thank you for your time in advance! I look forward to hearing any kind of response.

Undergrad: Top4 University in South Korea ( Sungkyunkwan University) Grad: current graduate std in the same university Major: Statistics GPA: 4.21/4.5 (undergrad,96.6%), Major GPA(4.33/4.5), 4.44/4.5( grad,99.5%) Type of Student: international Asian male GRE: Q: 166 (86%) V: 154 (63%) W: 4.0 (54%) TOEFL: (RLSW) 30 26 22 24 = 102 Program: Statistics or biostat PhD Research Experience: 1 published paper in Korean stat journal / 1 paper submitted / 1 paper in preparation two projects funded by national research institution of science 1 selected presentation in Korean Statistical society meeting LOR: One from my advisor(associate prof) in grad school, one from a korean assistant professor in US( I did a project with him or her), one from a professor( I took lectures from her or him) Under grad Courses: Calc 1 (A), Lin Algebra (A+), Analysis1 (A+), Matrix Algebra (A+) , math for statistics(A+: Calculus) , Intro of statistics(B+), Linear regression(A+), mathematical stat(A), statistical programming(B+), statistical Inference(A+: math stat2) , statistical data mining( A+), insurance statistics(A+), stochastic process(A), Experimental Design(A+), econometrics(A+), time series analysis(A+), Multivariate data Analysis( A+), Large data management and visualization(A), statistical simulation(A+), categorical data analysis(A+), spatial data analysis(A) Grad courses: advanced mathstat(A), advanced linear regression(A+), Advanced Multivariate statistics analysis(A+), Advanced math stat2(A+), advanced datamining(A+), Probability Theory(A+), Large sample theory(A+), bayesian statistics(A+), Convex Optimization(current) TA: intro to statistics / datamining / machine learning and statistical modeling/ statistical simulation / sample theory / basic and application of AI / BigData and Machine learning Awards : 5 awards of big data contest / 3 times Dean’s list Notes: What programs would be a reach/match/safety for me? I’m worried about my math background and English standard test scores.

Undergrad Institution: Top 3 South Korean University Major: Mathematics and Computer Science (Double) GPA: 3.97/4.0 Math GPA: 4.0/4.0 Type of Student: International Asian male Relevant Courses (A+ unless stated otherwise): Undergraduate level: Calculus I,II, Differential Equations, Linear Algebra, Analysis I, II (A), Modern Algebra I (A), II, Complex Analysis, Topology, Numerical Analysis, Discrete Mathematics, Graph Theory (A), Game Theory, Probability and Statistics, Probability Theory, Mathematical Statistics, Data Structures, Algorithms, Programming Languages, Automata Theory Graduate level: Real Analysis, Algebraic Topology, Combinatorics, Algebraic Geometry, Differential Geometry, Homological Algebra (A), Statistical Inference, Design and Analysis of Algorithms, Computational Geometry TOEFL:115; 30/30/27/28 GRE: 162/170/4.5 GRE Subject Mathematics: N/A Programs Applying: Statistics PhD Research Experience: - virtually no experience; winter research intern in deep learning, some research on graph theory but yielded no result Work Experience: - 2 years as data scientist at a Korean IT company Teaching Experience: Two CS courses, two times math olympiad TA Recommendation Letters: Three; one from a math professor, one from CS professor (who supervised a theoretical CS project which was quite successful but is unrelated to statistics), one from industry boss (senior data scientist, CS PhD) Programming skills: C/C++, Java, Python, SQL, Kotlin, HTML, Javascript, ... Research Interests: theoretical and mathematical aspects of statistics and ML Others: Several awards from nationwide mathematics and programming competitions, several fellowships and scholarships, (probably) funding for graduate study Applying to: Statistics PhD Stanford, Berkeley, Harvard, UChicago, UPenn, UWM, UMichigan, Columbia, Cornell, Yale, UCLA, ... Concerns: Not having relevant research experience/published papers etc. Not enough probability & statistics courses, no LoRs from statisticians Being an international student Hi everyone, this is my first post and I am quite worried about my PhD applications, because I could not find someone similar to me so I have no idea how strong or weak my application is. My biggest concern is the LoRs; I am quite sure that those letters will be strong, but they are not statisticians nor do they work in nearby fields. In fact, my interest was in pure mathematics 3 years ago, but 2 years of industry experience changed a lot (why I ended up in industry working as a data scientist is a rather complex story so I'd choose not to explain); this is why I didn't have meaningful interactions with statistics professors. These are my detailed questions: - Is it going to be a disadvantage not having any LoRs from statisticians? - As stated, I am thinking of getting the third LoR from my company boss. I also have another option of asking statistics professor who taught Probability and Statistics and Statistical Inference classes which I nearly aced. However, I thought the former is better because the professor has nothing much to say other than Did Well In Class, which is evident to the Committee from my transcript. Am I wrong? Should I get one from statistics professor even if the letter is going to simply say DWIC? I very much welcome any advice or feedback.

Hi People!! Undergrad Institution(s): 1. Top 35 private US university; 2. Top 25 public US university with a stats dept. with good reputations. (Transferred after freshman yr) Major(s): Statistics, Mathematics Minor(s): None GPA: 4.00 in major, 3.98 overall Type of Student: International Asian Male GRE General Test: V160, Q170, AW4.5 GRE Subject: Have taken all relevant courses (for the math subject test), not sure if I should take the exam Coursework (completed): Institution 1: Math: Calc. III (A), Probability (A), Discrete Mathematics (A) Stats: Intro. to Categorical Data Analysis (A) CS: Intro. to Comp. Sci. (A; java) Institution 2 (Undergraduate level): Math (all proof-based): Linear Algebra (A), Advanced Calc. I (A+; mathematical analysis), Probability Theory (A+, *weakly* measure-theoretic), Abstract Algebra (A+) Stats: Theoretical (Mathematical) Statistics (A+), Statistical Learning (A+), Bayesian Statistics (A), Applied Regression Analysis (A+), Computational Statistics (A) CS: Data Structure (A; in C++) Institution 2 (Graduate level): Regression Analysis (A; PhD level), Statistical Learning (A; PhD level), Linear Programming (A; master's level) Coursework (future): Undergraduate level: ODE (fall), Topology (fall), Measure Theory (spring), Convex Optimization (spring) Graduate level: Masters' Statistical Inference (spring), PhD's Probability (fall; may or may not drop it depending on the amount of measure theory needed) Research experiences: A UROP-like project in comp. bio., where I worked out a C++ program (2000-3000 lines of codes) for some structure prediction problems in biology. No letters, and no connections with stats. Honors thesis in causal inference (using a very classical statistical method instead of graphs); derived the test statistic for a hypothesis test that will be used in my thesis. Data analysis are yet to be done, but a thesis or at least a draft will be expected by the time of application. Summer research in selective inference; switched project once during the summer, so not sure if I have sufficient time to come up with any meaningful result to present. The current progress doesn't seem to be too promising whatsoever. But the work will be continued before my graduation. Research interests: Selective inference, causal inference, statistical machine learning, and interpretable learning pipelines in general. Letters of recommendation: Mentors of the two statistics research projects (I have also taken a course with each of them), expected to be strong or at least positive. (Planned) A Do-Well-In-Class letter from a PhD course instructor. Working experiences: NA, is that a big deal? Skills Languages: Python, R, C++, MATLAB, Java Teaching experience No, but planning to do something this fall. Schools: Reach: Washington, Michigan, Duke(?), Toronto(?); *completely* uncertain about my chances Match: Cornell(?), TAMU(?), UCLA(?) and programs ranked 15+ or 20+? Safety: Undecided, all programs seemed hard enough to get in Notes: At this time of the application season, I am worried about so many things, including my target schools and my chances of getting in. Much of my anxiety should be traced back to the following questions, and I will very appreciate answers to them!! How likely am I to get into any of these schools mentioned above? Are there any advices regarding school choices? How much will my international background hurt my chances of getting into PhD programs during COVID? I heard some programs are having financial issues lately. Is my math background too weak for a stats phd applicant? I know I should take measure theory earlier, but in my college it is only offered in spring semesters, which are after the application deadlines. So are there better ways to shore up my math background besides the two courses currently on my schedule (ODE & Topology) this fall? Should I find a tutoring job (which I am very interested in), prepare for the GRE math test, or take one more course (that being either complex analysis, PhD level econometrics, or PhD level probability, with estimated difficulty in that order)? Thank you guy very, very much for any help and support!

Undergrad Institution: US public university Major(s): Biology and Statistics Minor(s): None GPA: 3.16 Grad/Master's Institution: US private university Program: MPH Biostatistics GPA: 3.5 Type of Student: International Asian Female GRE General Test: Have not taken yet (planning to take late August) GRE Math Subject Test: NA Research Experience: · No published paper. · Research as part of master’s program (no thesis but presentation to faculty members and submitted a written report) · Research experience as a graduate student at the asthma center for a year – poster presentation to faculty & students Awards/Honors/Recognitions: NA Pertinent Activities or Jobs: · TA for one quarter of SAS course & one quarter of biostatistics II course (help students with lab hours, grade homework and lab assignments) · Stat consulting group (9 months) · Worked as a statistician/data manager at CRO (~3 years) · Currently working as a statistician in research hospital (~2 years) Letters of Recommendation: 2 professors from master’s institution, 1 manager from current work Coursework and grades(Math/Stat): Undergraduate Lower Division: Calculus I (A), Calculus II (A), Calculus III (B), Elementary of Probability & Statistics (A), Elements of Linear Algebra (B+) Undergraduate Upper Division: Statistical Methods in Biology (B+), Intro to Probability Theory I (A-), Intro to Probability Theory II (B+), Statistical Inference I (B), Statistical Inference II (A), Sampling Procedures Surveys (A), Intro Stochastic Processes (A), Regression (A), Adv Stat Package Data Analysis – SAS course (A), Master's/Graduate: Biostatistics I (A-), Biostatistics II (A), Biostatistics III (A), Analytical application of SAS (A), Research Data Management (A), Survival Analysis (A-), Intro Modern Nonparametric Statistics (A-), Applied multivariate analysis (A-), Survey & advance research methods (B), Advanced data Analysis (B+) Future Coursework (Fall 2021): planning to take Multivariable Calculus from nearby community college Programs Applying: I will apply to Stat/Biostat PhD programs (mostly Biostat PhD programs). Still not sure which programs, here are my tentative list: PhD Biostatistics · University of Pittsburgh School of Public Health · Vanderbilt University · Medical college of Wisconsin · Michigan State University · University of Texas Health Science Center--Houston · University of Washington · University of Michigan School of Public Health · Rollins School of Public Health · Chapel Hill School of Global Public Health · University of Pennsylvania · UCLA · University of Minnesota School of Public Health · University of Iowa College of Public Health PhD Statistics · Purdue University · North Carolina State University · UCR University of Wisconsin- Madison

Hello! I'm senior undergrad student in Asia. I will start Master program in my university, and then I will apply for Ph.d program in USA (maybe in 2024 fall). But I want to check my profile whether I took sufficient math courses and I want to get advise about school suggestion. Undergrad Institution: QS 80~90 Asian University GPA: 3.98/4.00 (total, 4.44/4.5), 4.00/4.00 (major 4.48/4.5) Type of Student: International GRE General Test: Q: 154 V: 168 W: 4 TOEFL: 28/26/23/26 (Total 105) Programs Applying: Statistics Ph.d Research Experience: 1 year of Research Assistant in computational neuroscience lab whose research topic is to make predictive models from fMRI image data using ML/Deep Learning techniques (such as LASSO or LOOCV). I helped statistical analysis in this lab, but I didn't make publications. I learned and did mediation analysis, ML techniques, dimensionality reduction techniques, and some Matlab and Python skills. Pertinent Activities or Jobs: 1 .5 year academic club in psychology department. I did research in this club and I was exposed and fascinated a lot of statistical methods from this club. Then, I decided to major statistics and mathematics. LOR: not dediced yet, maybe get stat professors in my university. I did good result(e.g rank 1 or 2) these professors' classes Math/Statistics Grades: Math courses: Calculus 1, 2 (A+/A+) Linear Algebra (A+, computation-based) Set Theory (A+) Analysis 1, 2 (A+/A+) Advanced Linear Algebra (A+, proof-based) Differential Equations (A) Partial Differential Equations (A+) Topology 1 (A+, Point-set topology) Topology 2 (A+, Algebraic Topology) Numerical Analysis (A+) Numerical ODEs (A+) Combinatorics (A+) Probability Theory(A+, undergrad, measure-based) Real Analysis (A+, Grad Lebesque Measure Theory + Some additional Functional Analysis topics) => Total 16 courses, 4.00/4.00 Statistics courses: Intro to Statistics (A+) Mathematical Statistics 1, 2 (A+/A+) Regression analysis (A+) Statistical Programming (A+, using R) Time Series Analysis (A+) Statistical Simulation (A+) Categorical Analysis (A+) Experimental Design (A+) Multivariate Statistical Analysis (A+) Stochastic Process (A+) Machine Learning (A+) Bayesian Analysis (A+) Nonparametric Statistical Analysis (A+) Advanced Mathematical Statistics (A+, Grad level Casella & Berger) Advanced Regression Analysis (A+, Grad level) => Total 15 courses, 4.00/4.00 Questions 1. did I take sufficient math courses? compared to other international students. Even though I majored mathematics, I did not take abstract algebra, number theory, or differential geometry because these things are quiet irrelevant with statistics. So I avoid these things. is my math coursework okay in terms of the number of courses and quality (e.g. proof-based, difficulty)? 2. which school can I target? Maybe I will publish two papers during master program. Considering my coursework, GRE, TOEFL, where can I target schools? I'm looking for NCSU, Penn state, Iowa state etc...but my school has no students who get admission there. But my profile is pretty good in my university. Help me! @Stat Assistant Professor and @bayessays!

Student Type: Domestic Asian Male Undergrad: Top 5 U.S Public School Major: Statistics GPA: 3.63 (Major GPA is 3.8ish) Math & stat classes: Linear Algebra (A), CALC III (A-), Differential Equations (A), Data Science (A), Optimization (A), Probability (A), Advanced Linear Models (this fall), Machine Learning (this fall), Stochastic Modeling (this fall). Intro to Programming (C+) I goofed in my Intro to Programming course (took it Freshman year), but I've done well in all my higher level stats courses that have used R so hopefully that makes up for it! GRE: 164Q, 160 V, 4.0W Research: None. Was accepted into SIBS this summer but got cancelled due to COVID. Letters of Recommendation: All three from my Stat professors. They should be decent. Hi everyone, I have been reading posts on this forum for a while and am looking for feedback. I'm looking to apply for BIOS graduate programs this fall but I'm not sure if I should be applying to PhD or MS programs. I would ideally like to apply for PhD programs (don't really want to pay for Grad school) but I don't think my application will be strong enough due to low GPA and lack of research experience. Applications: Currently looking to apply to Emory (MS), UNC (MS), UCLA (MS), UC-Denver (PhD), Houston Medical Center (Phd), Vanderbuilt (MS) Judging my profile, do you think I'm overrating or underrating myself? Should I only be applying to MS programs even at lower ranked schools (Denver, Houston)? Or do I have a shot at PhD programs? Other program recommendations would be greatly appreciated!

Hello everyone, I would like to apply math PhD fro fall 2022. I don't have a traditional background, therefore I would like someone evaluate my profile. Since there's a lot of uncertainty in 2021, much of the information here have their uncertainty as well. However I will update the information when the things are certain. Also any advice is appreciated. Undergraduate institution: East asian university in top 20 of qs ranking Major: Physics GPA: 3.25/4.0(overall) Math course: Calculus(A-), engineer maths(A), multivaraible calculus(B+/A-), Linear algebra (A-), topology(B) Graduate: One of the German Universities Excellence Initiative Major: Master of Mathematical physics Grade:1.47(German grading, 1 is the best, 5 is fail) Math course: Geometry of manifolds(1), representation theory(1), mathematical quantum theory(1.3), mathematical relativity(1), mathematical statistical physics(2), algebraic topology(taking), introduction to commutative algebra and algebraic geometry(taking), functional analysis(taking) Course plan to take in 2021: Introduction to real analysis, introduction to abstract algebra Research experience: 1. Working as a master student(research oriented) in my alma mater in theoretical physics for three years. 2. Undergraduate project on physics. 3. Working on master dissertation right now (C* algebra) LoR: My plan is one letter form my supervisor, two letters from the course I get 1. GRE: Not taken(may take it in 2021) GRE math: Not taken(may take it in 2021) Award: Two year scholarships for full time master student in my alma mater. type of student: International Asian male Type of PhD: Mathematics Research interest: Operator algebra, noncommutative geometry School I am planning to apply: UC Berkeley, UCLA, UCSD, Ohio State, Penn State, Purdue, Texas A&M, Vanderbilt U, U of Chicago Am I too weak for these schools? Anything I can do in 2021 to increase my chance? Thank You in advance!

Hey all, First and foremost thank you for reading my profile evaluation. I'd love to hear your feedback on my stats, the programs I've selected, my chances of admission, and if there are any programs that you'd suggest I consider given my profile. I am a student with a non-STEM background and I have the bare minimum prerequisite courses to apply to these programs (with good grades thankfully). I am hoping that through my GRE score and LOR/SOP (which I'm still writing) I'll be able to catch the attention of at least one admissions committee, and secure a spot in one of these programs. My ultimate goal is to acquire the technical background necessary to transition from Finance to Data Science. Thanks for your time, and I'm looking forward to hearing what you all think! Undergrad Institution: Large State school Decent/Good Business School GPA: 3.64 Majors: Business Admin - Finance GRE General Test: Q: 168V: 164W: 5.0 Relevant Course Work: Calculus I & II (A-,A) Business Stats (A-) Linear Algebra I (A) Intro to CS (A) By the time of matriculation (As in I'm planning on taking these in the near future): Calculus III, Multivariate Calculus Data Structures and Algorithms Type of Student: Domestic Student (native US) Programs Applying: Masters in Data Science mostly, some Masters in Analytics. My goal is to pivot careers into DS. Research Experience: None (as you probably guessed given my background) Letters of Recommendation: One great one from business capstone professor Two very good ones from internship in market research & Analytics department (One Data Scientist, One Marketing Manager) Work Experience: Analytics Intern (5 months)– became proficient with Alteryx, Tableau/Power BI. Experience in manipulating/transforming/cleaning large datasets which I'd then use to make dashboards and track KPIs. Started learning Python at the end of it under the tutelage of a full time DS. Financial Analyst (1.5 years by matriculation) – several high impact projects that look good on my resume. Lots of face-time with senior management explaining business impacts of whatever data I’m requested to work on. Used some Python scripting to automate reporting, built semi complex models in Power BI. My current list: NYU – Masters in Data Science University of Chicago - Masters in Analytics University of San Francisco - Masters in Data Science Brown – Masters in Data Science Georgia Tech – Masters in Analytics Northwestern – Masters in Analytics MIT – Masters in Business Analytics Carnegie Mellon University – Masters in Data Science Columbia – Masters in Data Science Duke - MIDS (Haven't researched this one that much yet) I feel that I'm reaching quite high, but am hoping that with some luck I'll hear back from at least one program. If anyone has any opinions or advice I'd love to hear it (even if the truth hurts). If you have a program you'd like to suggest, I'd love to hear that as well! Thanks again! Two_Dicey

Hi, all! I'm new here 😀 I'm graduating from Russian top master's program this year, and wish to apply for Ph.D. in Computer science in US for fall 2021. I am interested in Computer vision. I am really looking for help from kind people of GradCafe with my profile evaluation. Particularly, I am worried about my low GPA at bachelor. Bachelor institution: top-ranked Russian university. GPA: 3.0/4.0 Major: Data Analysis Master institution: other top-ranked Russian university. GPA 3.92/4.0 Major: Computer Science IELTS - 7.0 Type of Student = Muslim male Research experience: working as part-time researcher at my masters supervisor's lab 1 summer research internship at top Russian research lab in computer vision., Work experience: 1 industrial 6-month l internship one year as Computer vision engineer at photo-editing app start-up Publications: 2 so-so papers (one is first-authored) LoRs: first is very strong from my current research supervisor, second is from my summer internship supervisor, who is well-known in the field of computer vision. but we did not interact much, so he can't say a lot about me third is good from other senior researcher, I worked with Teaching: have a lot of experience in teaching as Lead TA and Lecturer Schools I like: (top) University of Virginia, UT Austin (medium) UIC, Northeastern university (low) Rochester institute of technology How are my chances? Am I good enough for these schools (at least medium and low ones)? Thanks in advance!

Hey, I've been browsing this forum trying to get an idea of where I stand. Eventually I realized I should just post my own thread. Thanks in advance for any help. Undergraduate Institution: large state flagship ranked around 150 Major: Finance, Math Minor: CS, History GPA: 4.0 Type of Student: Domestic White Male Graduate Institution: Same university (dual degree program) Masters in Applied Statistics GPA: 4.0 GRE Score: No GRE score yet - based on how I did on the GMAT, I expect to score mid 650 range for the Quantitative section Relevant Classes: Cal II (A+), Honors Cal III (A+), Intro Linear Algebra (A-), Regression Analysis (Grad - A), Multivariate Analysis (Grad - A), Economic Forecasting and Analysis (Grad - P because of pandemic) All of CS Minor were A's Relevant Classes Still to take this year: Real Analysis, Math Stats sequence, various applied statistics electives Research Experience: No formal math/statistics research - I have large personal projects related to modelling sports games to bet on for profit - tons of python code for scraping, analyzing, modelling data as well as optimizing certain functions (which I am very proud of) - In the last 10 months, I would say I spent probably 200+ hours on these projects Currently serving as a research assistant for some history professors writing a book already purchased by a large publishing company - I have done some basic statistical analysis for them with contingency tables, logistic regression, time series analysis Work Experience: I served as a TA for the introductory undergraduate statistics course at the university for one semester Letters: I have taken many history classes with this one professor who I am also acting as a research assistant for, as mentioned above, so I will get one from this person. Planning on getting statistics professors who have taught me and like me to write the other two - they aren't big names or anything, but they should write good letters Statistics PHD programs I am thinking about: Washington, Columbia, Michigan, NCSU, UCLA I just recently started checking into programs that would fit my interests. I haven't really done an exhaustive search of programs yet - I wanted to get feedback on where I stand first. Some questions for you all: 1) Do I have a chance with programs as good as Washington or Columbia? 2) Are there any schools that have more of an applied focus that I should be looking at? 3) Should I take the Math GRE? I think I could study enough to get a decent score if it is worth the effort Thanks for any help in advance!

Background - College: B.A. Economics GPA: 2.7 A huge part of the low GPA is because of depression in college. I began isolating myself a lot and because of the stigma of mental health in my community I was reluctant to seek help. When I did I was too scared to go back after 1 appointment. I have since taken several courses post under grad (which I aced ) and currently taking graduate level courses and sought therapy. I have learned so much about myself and how to balance work, school and my social relationships. Work Experience: Total of about 3.5 years in Accounting Volunteer Experience: Interned for a non profit, general volunteer experience (food bank, hospital volunteer, outdoor museum, social media) Why an MSW?: I've always wanted to be in a profession where I would be able to help people and understand why they did something, their circumstances and their culture. I think working in business has taught me a lot about the intersectionality between business and org psychology as well. Inclusion and diversity has always been a huge part of my value. Another part is that psychology was a field I had always wanted to major in since college, but with mental health being taboo in my community (especially with my parents), I appeased my parents and majored in business. This particular divide between my parents and I made me realize that I want to be the person for my younger self and that it's okay to ask for help. My goal is to apply to Cal States within California.

Hi everyone! I just wanted to post my stats and figure how I stack up! Student Classification: Domestic White LGBT Male Undergrad: R1 Large state school, US News top 150 Major: Statistics Minors: Math, Economics GPA: 4.00 Relevant Coursework: (All A, no A+ system) Math Coursework: Calc I-III, Diff Eq, Linear Alg, Mathematical Modeling(has some analysis) Statistics Coursework: Stat Methods I-III, Stat Theory/Probability I-II, Statistical Computing, (the following are 4000 level electives): Biostat methods, Sampling Methods, Categorical Data Analysis, Bayesian Analysis Computer Science Coursework: Intro to Programming, Numerical Calculus, Security Methods for Computing Economics Coursework: Intermediate Microeconomics, Intermediate Macroeconomics, Econometrics I Real Analysis is not offered at my school until the graduate level, I don't know if that is common but I worry that my coursework is a bit weak/too general considering the programs I'm interested in. Research Experience: 2 years of undergraduate research in machine learning, using Bayesian statistics and estimators. (2 first author publications) 2 Semesters of independent school-funded research in IEMS (poster presentation at conference) 1 Semester of research in data science with professor 1 REU in data analytics GRE General Test: 166Q, 160V, 5.0W Awards: Nothing except purely academic, i.e. Summa Cum Laude, Top Dean's list every semester, etc. LOR's: 1 Super strong, 1 Strong, 1 Average (Based on general estimation.) In order: From relatively well-known IEMS professor I did my two years of research with. From REU I did over a summer. From professor I did my one semester of research in data science with. Applying to: Statistics PhD. Also would be willing to apply to Statistics MS if it would better prepare me for PhD coursework. Honestly, I'm a bit unsure of what I want to specialize in as far as research goes. I enjoy machine learning/optimization, econometrics, and statistical computing. I'm not a fan of biostatistics, so that helps me narrow it down. Schools: CMU(Machine Learning + Statistics), UChicago(Econometrics + Statistics), Berkeley, Duke, UNC Chapel Hill, UPenn Thoughts: I think that my coursework is my weakest area, and my research is my strongest area. I'm very open to hearing about other schools that would also fit my interests. CMU is definitely my top choice right now, because I have the most experience in this area of research and their program really interests me. The rest are mostly thrown together through light research and recommendations from professors. Any guidance/advice/evaluations would be super appreciated!

Heyo yall, I'm currently applying to some PhD programs in stats and I'm trying to gauge how competitive I will be. Undergraduate Institution: R1 state school, top 100ish US News, not particularly well-known Major: Mathematics and Economics Minor: Data Science GPA: 4.00 Type of Student: Domestic white male (I am not straight tho I have absolutely no idea if I should include this on my app) Research Interest: Econometrics, applied statistics in social sciences, ML GRE Score: 168Q/160V/4.5, no math subject test cause it was canceled Math classes: Calc III (A), Basic Concepts in Math, an intro to proofs class (A), Real Analysis I and II (A), Linear Algebra (A) Stat classes: Probability theory I (A), Probability Theory II (A), Mathematical Statistics (A), Data Analysis and Stats Computing (A), Intro to Machine Learning (in progress) Misc classes: Mathematical Economics, basically a lot of linear algebra and its applications (A), Econometrics I and II, at the graduate level (A), Python Programming (A), more programming and data science courses (in progress) Research Experience: Year-long research grant in econometrics, leading to a paper (not published) but presented at a conference Currently a research assistant, using Python to do natural language processing in the social sciences, currently drafting a paper on Machine Learning techniques that coincide with this project Work Experience: Just some work as a data manager Sophomore year to pay some bills Awards: Dean's list all semesters 2nd prize for Econ paper in my department Letters: Currently deciding on three of the following, in order by how strong I think they'd be: Sociology professor who I am working with right now, publishes applied sociology papers Econ professor who I worked with on my econometrics paper, publishes applied econ papers Math professor in all of my proofs class including real analysis where I was one of the best students, does not publish anymore Math professor in prob theory II where I succeeded after going to office hours a lot, publishes stats papers Schools: University of North Carolina, University of Chicago, University of Washington, UPenn, Wisconsin-Madison, UCLA, University of Toronto, University of Michigan, Colombia, Carnegie Mellon, Penn State, Iowa State Any other school suggestions/letter suggestions or any other suggestions would be greatly appreciated! Thanks yall

Undergrad institution: NYU Major: Honors Mathematics GPA: ~3.7 Domestic/International: domestic. Research Interests: Probabilistic time series analysis, bayesian stats, reinforcement learning, deep learning. Humanitarian slant. Undergrad Math Courses: Honors cal III (B+), honors LinAl (A-), Indep Study in classical diffgeo (A), ODEs (A-), honors analysis I (A-), honors algebra I (A-), independent study in representation theory (A), honors analysis II (functional analysis and measure theory, A), honors algebra II (B+) independent study in wavelet analysis (A). Grad Courses: Measure theoretic probability (A-), topology II (A). Current Courses: math stats, math modeling, [PhD/MA] probabilistic time series analysis, [PhD] probability 1, [PhD/MA] (mathematical) foundations of machine learning. Research: Current work in multigrid methods and machine learning. Unlikely to be published. Two undergraduate research grants from department and dean. Letters of Rec: 1 very large name in probability (ex Bourbaki), two other TBD but decent to very good professors. Programming languages: Python, R, Matlab, some C++. GRE: not taken due to COVID. Work: internship at bulge bracket bank starting October. Schools: Generally top programs, especially with a focus on humanitarian statistics. Notably: Columbia Stanford Harvard UChicago I dislike safety schools, if I'm reaching too high would rather spend a year in industry then apply again. Some recommendations of schools would be appreciated though. My biggest concern is that my transcript seems distinctly A-. Research was self guided and with overseas professor who could rarely communicate due to covid, as well as a topic my research partner and I fell out of love with quickly. Also, my honors analysis and algebra II courses were way harder than usual ones, with the analysis class being very similar to Courant's PhD real analysis course. Also had a particular... disdain for algebra professor that I'd rather not write on my SoP which is a large part of the B+ in that class (genuinely, not just whining).

Hello everyone, I am planning to apply for PhD programs in Statistics and/or Biostatistics. I am seeking advice about the programs I should target. I would like advice based on my background below. Thank you a lot for your time! A quick summary about me - I have undergraduate degree in environmental science and master’s degree in applied stat. I graduated in 2019 and have one-year work experience. I attach my questions at the end. Type of Student: International, Asian Undergraduate Institution: Asian, top-50 by US news ranking Majors: Environmental Science GPA: 3.46/4.0 by WES (84/100) Courses taken (score by WES): CS Intro to Computation (A) Data Structure and Algorithm (B) Math 2 calculus courses (A and B） Linear Algebra (A) Probability Theory and Statistics (A) Stat Applied Statistics (B) Graduate Institution: Master’s degree, top-20 by US news ranking in stats major Majors: Applied Statistics (courses only, no thesis), dual degree in environmental science GPA: 3.6/4.0 Stat 400-level Intro to Theoretical Stat (B+) Applied Probability (B) Stat 500-level Stat Learning I (A-) Stat Learning II (A-) Stat Inference (A) Stat Consulting (A-) Probability Distribution Theory (A-) Stat Inference (A) Stat 600-level Linear Models (B+) Survival Time Analysis (A) Stat Computing (A-) GRE General Test: Q: 170 (96%); V: 152 (56%), W: 3.5 (41%) Research Experience Second author of a paper that is under peer review now. I did plenty of map visualization on the topic of air pollution. No modern stats method applied. (*big name prof. in biostatistics, not sure how the rec would be) One presentation at the School Symposium about a minor project, using spatial statistics method to answer an environmental question. Undergraduate thesis is about applying non-linear optimization method in a environmental problem. (*prof. in environmental science, good but not strong rec) Graduate capstone is much like consulting about clean energy, no related to stat. (*prof. in environmental science, might be strong rec) Research assistant for a social scientist for half year. I mainly cleaned data in R and SAS, and did some simple tests. (*prof. in social science, strong rec) Working Experience One-year work experience in a software company. Daily work includes programming in Python, R, Git; researching for spatial-temporal statistical methods, such as time series forecast, spatial outlier detection. (*supervisor) Letters of Recommendation I listed the potential recommenders with asterisk* in the Research/Work Experience above. I can reach out to prof. who taught stat courses but that would be weak rec I guess. Currently considering schools Planning to focus on 20-50 tiers schools in the U.S., such as UCLA, UC Irvine, UC Davis, OSU, Boston U, UUC. In addition, I am planning to apply for British Columbia and McGill in Canada. My questions Here is my main question - I like statistics, and based on by background in environmental science, I think biostatistics would provide a good balance between theory and application for me. Yet with little research experience in biostats, I find it hard to compare the programs. What should look for when I scan through the programs? Any advice about how to filter programs would be appreciated! I have another concern about the targets – I am worried my low GPA and weak background in math would become a constraint. Is there anything I should be aware about? For example, does programs usually filter applicants' GPA first? In addition, I would love to hear about who you think would make the best combo of recommenders. The fact that most of my rec would not come from prof. in stat concerns me as well. Thank you in advance for your input!

Undergrad Institution: University of Washington Type of Student: asian male, International (undergrad in US) Major: Data Science and Statistics Minor: Computational Finance GPA: 3.8 (Major is 3.7) GRE General Test: Q: 166, V: 157, writing 4.5 Research: Some research on COVID-19, no publication. Working on honors thesis. Teaching: TAing an undergrad course Experience: Statistics related volunteering, data science blogger Awards: 1st place in a Datathon (~60 participants). A programming certification by Google Letters of Recommendation: 1 from research supervisor (professor). I will ask thesis advisor (professor) and TA supervisor for the other 2. Relevant Coursework: All undergraduate level. linear algebra, differential equations, probability, machine learning, statistical learning, discrete & continuous modeling, database Schools Applying (PhD in Statistics): University of Washington Carnegie Mellon UC Irvine UC Davis UC Berkeley UCSB UCLA Columbia NYU University of Toronto UBC Any school recommendations can help, thanks!

Undergrad Institution: Big state school (CSU) Major: Economics Minor: Math GPA: 3.835 (Magna Cum Laude, 4.0 if looking at just last 60 units) Type of Student: Domestic White Male GRE General Test: Taking it in a few weeks, have done very well on practice tests so I believe I can get 165+ Q and 160+ V at the very least - AWA probably 4.0+. Also willing to retake it if necessary. Programs Applying: Statistics PhD (but not necessarily opposed to biostatistics) Research Experience: Nothing unless you count an econometrics capstone project. Only decided to go beyond undergrad within the last semester or so. Awards/Honors/Recognitions: Very likely that I will be awarded as the top/outstanding Economics student, however that award seems to not be happening/has been delayed due to the covid situation. Letters of Recommendation: Very strong letter from the calc-based probability and real-analysis professor. Strong (or better) letters from calc-based mathematical stats, proof-based linear algebra, and econometrics professors. I can go into more detail about these professors on request. Math/Statistics Grades: Calc I (B+), Calc II (A+), Calc III/Multivariable (A+), Real Analysis (A+), Linear Algebra (fairly proof-based) (A+), Proofs Class (been told it's akin to a slightly more advanced discrete math class) (A+), Calc-Based Probability (A+), Calc Based Mathematical Statistics (A+), Econometrics (A+), Basic Stats Class (A+) Schools: Any recommendations here can help, but my main goal is to attend a decent UC and UC Irvine specifically is my current target (are programs in the top 30-60 range a reach for me? Should I consider a Master's instead?).

Type of Student: International (Canadian) Undergrad Institution: Top 5 Canadian University Majors: Honours program in Comp Sci. + Stats Minor: Physics GPA: 3.75 GRE: 160V/164Q/4.5 Research Experience: 3 REU's, two of which resulted in honours theses (one CS thesis and one Stats thesis). Although I have no publications, one of the REUs resulted in a paper that is currently being worked on and will probably be submitted post-application, if that matters. Also, I wrote a "project paper" that uses tools from stochastic PDE's, analysis, and topology to prove the behaviour of stochastic algorithms which impressed a prof. I was thinking of creating a personal website to showcase these theses, projects, etc. Graduate Courses: I will be graduating with 8 graduate courses (2 of which are PhD courses): Time Series(A), Generalized Linear Models(A), Mathematical Topics in Machine Learning(A), Applied Machine Learning(A), Regression and ANOVA(A), Reinforcement Learning,(*) Computational Statistics(*), Probabilistic Algorithms(*). * denotes currently enrolled Relevant Undergrad Courses: Honours analysis I (A), Honours Analysis II (B), Honours Linear Algebra (A-) Honours Stats (B+) Abstract Algebra I (A), Other: Awarded a fellowship to conduct research over the summer. Elected into student council twice and volunteer teaching music lessons to elementary kids. Letter of Recommendations: I currently have 4 professors who said they are very happy to write letters for me. Two of which said they will write "excellent" letters for me. All the profs are well-known in their respective fields. Notes: Hey guys! I'm mainly applying to PhD programs in statistics and concentrating on the following programs (they may be a reach but fingers-crossed): 1. CMU 2. UCLA 3. University of Washington 4. Yale 5. University of Toronto In short, I think my weak points are my GPA and GRE. I'm hoping my letters and the fact that I performed well in advanced courses can compensate for them. I essentially completed a masters degree during my undergrad so I feel like I wouldn't get much out of applying to a masters program. If anyone could give their opinion on schools I am competitive for and what other programs I should look into, that would be greatly appreciated! I'll take any information on biostatistic program stoo! My backup is a masters at my current institution which I am confident I can get into. Thanks and good luck to everyone else applying!

Undergrad Institution:- A State University in India ( Country Rank:- 151-200) Program:- Bachelor of Science (Hons.) [ 3 year ] Major:- Statistics Minor:- Mathematics, Economics GPA:- 10/10 (Major), 9.6/10(Overall) [ Best Science Undergrad Award ] Type of Student:- International Asian Male Math & Stat Courses:- Classical Algebra+Trigonometry(9/10), Coordinate Geometry+Vectors(9/10), Calculus(10/10), Mathematical Analysis (10/10), Diff. Equations (9/10), Abstract Algebra(10/10), Linear Algebra+Mechanics(9/10), Numerical Analysis (10/10), Probability-I, II, III, IV (10/10 in all), Stat. Methods- I, II (10/10), Stat. Inference-I, II (10/10), Applied Stat I (10/10), Stochastic Process+Biostat+Applied Stat (10/10), Sample Survey(10/10), ANOVA+Design of Expt. (10/10), Multivariate Analysis+Operations Research (10/10), C Programming (10/10) Research/Internship:- One summer internship in a reputed institute (learnt some advanced math), Bachelor Dissertation on Skew-Normal Distribution (literature review+one new direction discovered by me) Graduate Institution:- Indian Statistical Institute Programs attended:- Master of Statistics [ 2 year ] Percentage:- 71/100 Courses:- Analysis-I (51/100), Linear Algebra+ Linear Models (83/100), Prob. Theory (75/100), Measure Theoretic Prob. (66/100), Martingale Theory (67/100), Large Sample Theory (69/100), Stat. Inference-I (58/100), Stat. Inference II (70/100), Robust Statistics (72/100), Non-parametric+Sequential Analysis (74/100), High Dimensional Inference (73/100), Regression (71/100), Multivariate Analysis (75/100), Sample Survey+Design of Expt. (64/100), Intro Computer Programming (75/100), Time Series (76/100), Stat. Computing-I (75/100), Stat. Computing-II (73/100), Pattern Recognition+ML(70/100), Resampling Techniques(70/100) GRE(general):- 158 (Verbal), 169 (Quantitative), 4 (AWA) GRE(Mathematics):- 77 percentile Research/Project:- Many projects as a part of course. One 6 month project paper on High-Dimensional Inference LORs:- Good Programs applying:- PhD Statistics(main preference) + PhD Bio-statistics(those where I can find work related to my graduate project) Schools:- Any recommendation for both the programs will surely help me. For Statistics, I am aiming for some universities like University of Texas, Austin, University of Connecticut, University of Iowa, Iowa State, Ohio State type of universities.

Student Type: Senior Student. Undergrad: US News top 40 private university Major: Economics, Mathematics, International Studies GPA: 3.96 Math Courses: Cal I, II, III; Differential Equations (A), Probability (A), Stats Theory (A), Linear Algebra (A), Introduction to Proof (A) Also took Econometrics (A). GRE: V 164 Q 169 W 4.5 Letters of Recommendation: two academic recommendation letters from my econometrics professors. One that taught me econometrics and one that I TA-ed for. One professional recommendation letter may come from my previous supervisor in the state government treasury department. My Worries: Is recommendation letter from econometrics professor enough for applying to Stats master programs? My math courses were mainly taught by PhD fellows, and I was not familiar with the few math professors that taught me. Also, I was wondering whether a recommendation letter not from a directly stats-related internship helps in my application. Meanwhile, do you guys think I should take real analysis in this semester?

Hi everyone, I finished undergrad in Spring 2018, have been working in consulting for 2 years and am looking to enroll in either a masters or PhD program in Biostatistics. I would prefer the PhD route upfront in the interest of funding. I've been preparing for the last year or so, and I would appreciate some more guidance on setting expectations and moving forward. My math courses are a little light, but I did have exposure to some statistics applications in finance/econ courses. I studied chemistry my first two years of undergrad and have some background in medicine / public health from those days, which I've addressed in my SOP when relevant. Type of Student: Domestic male Undergrad Institution: top 50 university (USNWR) Major: Finance GPA: 3.88 GRE General Test: Q: 166 V: 167 W: 4.0 Research Experience: None Letters of Recommendation: Two from finance professors, should be solid. One from a director at my company with whom I've worked closely and performed well. Math/Related Grades: Calc II (A), Predictive Modeling and Optimization (A), Financial Modeling (B+), Econometrics (A), Calc III (B), Linear Algebra (A), taking Diff Eq this fall. Programming: I have background in R from taking econometrics. Planned Applications: UCLA (MS), UC Berkeley (MS), University of Wisconsin-Madison (PhD), Boston University (PhD), Emory University (PhD), Columbia University (PhD) I realize a course in real analysis and/or probability would help a good bit. Unfortunately, one or two classes a semester is the most I can manage with my current job. If I'm not admitted, I am fine to re-apply for Fall 2022 admission and use the year to further strengthen my app. Any recommendations on programs or other advice is very helpful. Thank you!

Forgot to tag my previous post, and couldn't figure out how to add the tags, so I'm reposting. Undergrad Institution: Smaller school (St. Louis University) Major: Math Minor: CS GPA: 3.97 (Summa Cum Laude) Type of Student: Domestic White Male GRE General Test: Have not taken yet, though I expect high scores. Programs Applying: Statistics PhD or Math PhD Research Experience: Some in Number Theory. Was working on a paper, but COVID interfered big time. I'm working on it again now. Hopefully I can finish soon. Awards/Honors/Recognitions: Received our school's award for the top performing math student. Letters of Recommendation: My academic advisor, who I believe thinks very highly of me. My Number Theory professor/research advisor (a little worried about his if I don't finish the research paper). Professor from my Bayesian Statistics class, who I believe thinks very highly of me. Professor from undergraduate and graduate Analysis, who I'm confident thinks very highly of me. Math Grades: (All A's) Calc II-III, Linear Algebra, Intro to Proofs, Geometry, Differential Equations, Complex Variables, Nonlinear Dynamics and Chaos, Number Theory, Advanced Undergrad Algebra and Analysis, Advanced Linear Algebra, Metric Spaces, Graduate Algebra and Analysis (Fall 2020) Statistics Grades: (All A's) Foundation on Statistics, Probability Theory, Bayesian Statistics CS Grades: (All A's) Intro to Scientific Programming, Intro to Object-Oriented Programming, Data Structures (Fall 2020), Machine Learning (Fall 2020) Work Experience: About two years as tutor for athletes, a semester as a Learning Assistant for Pre-Calc, a semester as a Teaching Assitant for Calc I, and another semester as a TA for Calc II (Fall 2020). Schools: Looking for recommendations for Statistics options. Stats: WashU, UW-Madison, UMinnesota-Twin Cities, UMass-Amherst, UConn Math: UChicago, UW-Madison, Brown, North Carolina State University, SLU Hey everybody. I am a senior math major. I've spent the last four years planning to do pure math. But in the last few weeks I've been seriously considering instead doing computational statistics, or Machine Learning. Still haven't decided. A large factor will be whether or not I can get into a good grad school for math. I'm looking for any advice you can give on school recommendations. I'm trying to apply to very few places. My financial situation is good enough not to qualify for support, but bad enough that I would really like to not spend much at all on application fees. Also, for schools not requiring the General GRE, how bad would not taking it be? I'd like to avoid costs there as well, if possible, though I believe it may not be. For my recommendation letters, I'm going to talk to my advisor to get more personalized help/advice.

Hey everyone, I just graduated college, and due to COVID, my plans have changed. Originally, I was going to work in a sports analytics role for a professional baseball team this summer/winter with the chance of being hired full-time if I performed well. Then, after a year or two of work, I was going to apply to grad school. But, my job got canceled, and so now I've been home coaching pickleball (no lie, it's been a fun experience) and have decided to apply to grad school this winter. Thanks for any help you can offer! Undergrad Institution: UC Berkeley Major: Statistics GPA: 3.743 Type of Student: Domestic White Male GRE General Test: Taking it in a few weeks, obviously hoping for 165+ Quant Programs Applying: Master's Statistics Research Experience: I had a negative research experience with a professor, and I ended up not passing the "research apprenticeship." This is one of the main dents in my transcript I feel, so I will probably address it in my applications. While I don't think the professor did his fair share in leading the apprenticeship and he admitted this, I definitely could've done things better too. Fortunately, I grew a lot from the experience, and he and I met a semester later and reconciled, leaving everything on good terms. Work Experience: Does this matter? Just thought I'd mention--I was a data analyst intern for a baseball team after my sophomore year (used lots of R and SQL). After my junior year when I went abroad, I was a business analyst for a pro soccer team (mostly used Excel). This position was not a great experience, and I actually quit the role to go back to school early over the summer to prepare for senior year. I used this time to study machine learning on my own to be ready to apply to jobs, and I ended up getting the job I mentioned above with another pro baseball team. To this day, I'm really happy with my decision to leave the soccer job and do something that would be beneficial for my career. Awards/Honors/Recognitions: I was selected as a TA for Berkeley's 1,000 student Intro to Data Science course, which involved me teaching weekly lab and discussion sections of 25 students and participating in weekly meetings about content and logistics. I taught topics like python, SQL, pandas, linear regression, and PCA. I did this my last semester. Letters of Recommendation: Going to request a letter from my Game Theory professor who knew me personally and definitely liked me. Got an A in her class. Also will request a letter from one of the professors I TA'ed for (mentioned above). The third letter will probably be from an employer, though I'm a bit torn here. I can ask the person from the baseball team who hired me and who can speak to the models I built throughout the hiring process and my performance in interviews, or I can ask my current employer (the pickleball director) who I'm sure would have good things to say. Math/Statistics Grades (freshman-senior year in order) Intro to Linear Algebra and Differential Equations (B), Calc III/Multivariable (A), Calc-Based Probability (B+), Computing with Data (basically an R class) (A+), Discrete Mathematics (intro to proof-writing as well) (A), Theoretical Linear Algebra I took one summer at UCLA (A), Intro to Real Analysis (B), Calc-Based Mathematical Statistics (B), Fundamentals of Data Science (the class I TA'ed for) (A-), Intro to Time Series (A), Linear Models - Theory and Applications (A), Game Theory (A), Intro to Machine Learning (very theoretical) (A). Regarding my grades, I definitely didn't do as well as I would've liked in some of the fundamental stats courses (probability, mathematical statistics). But, my senior year I got all As in my stats courses which I really worked hard to do, and I hope this shines through. There are some weak spots in my math grades too, like my Linear Algebra and Diff EQs class, but that was my first semester and I like to think my A in the summer Linear Algebra class makes up for it. Real Analysis was really tough and I took it during a difficult semester personally, and it basically showed me I don't want to do a PhD. Schools: I'm very interested in applying to a few schools in Europe... please let me know if you know anything about this. And, regarding schools in general, I'm not quite sure which tier of schools I should attempt to target. From what I've read, Master's in Stats aren't too terribly competitive, so I'd like to think I can get into a top 20 program. Thanks for any guidance here. - ETH Zurich - EPFL (in Lausanne, Switzerland) - Oxford/Cambridge? (They seem pretty expensive for European programs) - Stanford - Berkeley - Harvard Data Science - Washington - NC State - UNC Chapel Hill - Minnesota - UCLA - Yale