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  1. Hey everyone! Hoping to get an idea of the strength of my application and chances of getting into some of the schools below for a PhD. Left school to work at a management consulting firm which I believe is a bit untraditional. Would also appreciate any school recommendations/adjustments to my current list, any thoughts welcome! Thanks Undergrad Institution: Top 10 University in Canada Major(s): Data Science GPA: 3.96 (Last 4 Semesters/2 Years), 3.96 (Major), 3.89 (Cumulative) Type of Student: Black International (Canadian) Male GRE General Test: Taking summer 2022 Programs Applying: Computer Science (PhD), Statistics (PhD), Operation Research (PhD) Research Experience: 2 first-author ACM conference papers (1 applied machine learning and has been cited, 1 data/text mining) 1 last-author conference paper (data/text mining; awarded Best Track Paper in Data Analytics and Big Data) 1 journal publication in geospatial statistics (submitted) Other research in applied machine learning and finance (no publication) Awards/Honors/Recognitions: Gold Medal (graduated with the highest GPA in Major, top of the class) Undergraduate Fulbright Fellowship Letters of Recommendation: One strong letter from an Associate Professor in Statistics & Management Science who I wrote the geospatial statistics paper with (not well-known in CS) One strong letter from an Assistant Professor in Data Science & Business Analytics who I published two papers with in data/text mining (not well-known in CS) One decent/strong letter from an Associate Professor in Economics & Statistics who I performed research with (~1yr together) but no publication One strong letter from a Partner at my management consulting firm (relevant for Operations Research programs) Computer Science Courses: Intro CS I & CS II, Data Structures & Algorithms, Software Tools & Systems, Discrete Structures/Discrete Math, Analysis of Algorithms, Databases I, Data Science I Math/Statistics Courses: Probability & Stats I & II, Statistical Programming, Calc I, Calc II, Intermediate Calc I, Intermediate Calc II, Linear Algebra I, Linear Algebra II, Numerical Analysis, ODEs, Modelling and Simulation, Regression, Generalized Linear Models, Advanced Statistical Computing, Statistical Learning Any Miscellaneous Points that Might Help: Particularly interested in doing research within the field of Machine Learning (and potentially NLP), still figuring this out. Not particularly interested in CV or RL. Would have spent >1 year at a management consulting firm at the time of applying and >2 years by matriculation (a advantage/disadvantage?) Applying to Where: In no particular order here, CMU - PhD in Machine Learning University of Washington - PhD in Computer Science Columbia - PhD in Computer Science MIT - PhD in EECS Princeton - PhD in Computer Science Cornell - PhD in Computer Science NYU - PhD in Data Science UIUC - PhD in Computer Science UT Austin - PhD in Computer Science UPenn - PhD in Computer Science UC San Diego - PhD in Computer Science UCLA- PhD in Computer Science Georgia Tech - PhD in Machine Learning UMichigan - PhD in Computer Science CMU - PhD in Statistics University of Washington - PhD in Statistics Stanford - PhD in Statistics* Cal Berkeley - PhD in Statistics UPenn - PhD in Statistics Yale - PhD in Statistics & Data Science Stanford - PhD in Statistics Cal Berkeley - PhD in Statistics UPenn - PhD in Statistics UMichigan - PhD in Statistics CMU - PhD in Operations Research MIT - PhD in Operations Research Georgia Tech - PhD in Industrial and Systems Engineering UMichigan - PhD in Industrial and Operations Engineering Thanks again!
  2. Hi all, I'm currently working, but have decided to apply for a PhD program this Fall in statistics. I'm quite anxious about the chance of being admitted, since I have virtually no research experience. Below are my background. Undergrad: UIUC Major: Actuarial Science GPA: 3.98/4.0 Master: Columbia Major: Statistics GPA: 3.67/4.0 GRE: 330 Research: Some grad-level course projects, a small undergrad-level educational research, currently doing an econometric research to improve my weak research experience. Work experience: Currently working as an actuary in a top leading insurance company. Recommendation letters: One from actuarial math professor in UIUC, one from statistics professor in Columbia, another is from the econometric research advisor(instructor tile, but a Harvard and UChicago alumni) Course taken: Most math and stat courses and machine learning courses that should be prerequisite for applying for a stat PhD, but haven't taken real analysis yet. Others: Nearly passed all associate level actuarial exams Pros: Relatively good math skills, have a master's degree, (some work experience?) Cons: No concrete research experience, no publication, no hardcore math courses such as real analysis, low graduate school GPA Schools I plan to apply are as follows, 15 in total, I'm not sure whether I'll be rejected by all of them due to lack of concrete research experience. Actuarial Science PhD: Waterloo, Wisconsin-Madison, UIUC Statistics PhD: UCLA, UMichigan, UCSB, UCD, PennState, 7 undecided (Probably from USnews top 50~150 list) Also, is it common for being considered and admitted for MS instead(when the committee believe a student need take more prerequisites) when applying for PhD? Any advice will be precious for me. Thanks a lot!
  3. Context: I am a third-year undergraduate statistics and computer science major and I am interested in pursuing a statistics PhD. I plan on applying to graduate programs next fall. Earlier this semester my family and I got COVID and this really put me behind in all of my classes, and the one egg I dropped whilst playing catch-up was my real analysis class. I bombed both exams, and there is really only the final exam left which can affect my grade. After bombing the exams I switched the class to a Pass-Fail grading option. I did talk this through with my professor, and I am on track to still pass the class considering how much work I have already put in. However, it realistically can at best be a C+/B- depending on the final exam score. From meeting with graduate students I know, I am under the impression that this course is heavily weighted in admissions for statistics programs. Should I stay in the class and let the grade resolve as a Pass or drop the class entirely and take it a second time? Would applying with real analysis absent from my transcript entirely be better than saying I "merely passed" the class? Does that fact the we are still in a pandemic still hold any weight?
  4. Hi all, Here is the link to a server for Statistics MS applicants : https://discord.gg/54AXtbuQ9F Feel free to join and hear from others on decisions, grad school advice, and more!
  5. I saw last year's post and thought it would be a nice time to start an application thread. Additionally, I believe emails for interviews for PhD biostatistics programs have started rolling in.
  6. Undergrad Institution : Top 5 public university (US News) Major(s): Statistics, Mathematics, minor in Physics GPA: 4.0, haven't graduated yet Type of Student: Hispanic male, domestic Programs Applying: Statistics PhD, Fall 2023 admission Courses taken: Calculus I-III, Differential questions, Modern Physics, Mechanics I, Data Structures and Algorithms, Electromagnetism I, Regression Analysis, Intro to Probability Theory, Sets and logic, Discrete math, 3 linear algebra courses (computational, proof-based, data science applications), Design of Experiments/ANOVA, Statistical Theory / Mathematical Statistics Currently taking and plan to take: Time series analysis, a second probability course (stochastic processes, probability spaces), Abstract Algebra, Categorical Data analysis, Real Analysis I-II, Nonparametric statistics, Statistical computing, Statistical learning, Complex variables GRE General Test: Haven't taken yet Research Experience: Worked with a radiation oncology professor in a project involving proton therapy, mostly did literature review until I realized it wasn't my thing and left. Currently doing applied time series analysis with a statistics professor. I am the primary author for a current paper and it could be published. Pertinent Activities or Jobs: TA for a research course, mentor for an undergraduate research program, tutoring chair for a Physics society chapter Awards: Dean's list / Presidential honor roll some semesters, a merit scholarship Letters of Recommendation (prospective): Two from statistics professors. One is my research mentor and the other is one who I believe can write me a strong letter. Third will probably be from a mathematics professor. Miscellaneous skills & points: Haven't taken any graduate courses yet and don't plan on it, but that could change. I have a few years of programming experience and have a few projects listed on my resume in various languages, including GUIs, implementations of B-spline and Bezier curve interpolation and visualization, and large-scale machine learning and AI. I switched into the math major sort of late so I won't be taking much after Real Analysis since I'm doing it my senior year. Schools applying to: This is where I'm the most lost as I'm not sure where I should be applying to. A preliminary list is UW Florida State U of Michigan CMU Penn State Ohio State Too early to say what I'm interested in exactly but I think that any school with a presence of Bayesian statisticians would be nice. My process for picking schools was looking loosely at USNews rankings, seeing if they had professors doing stuff I have marginal interests in, and weighing in whether I would want to live in the area. I also started looking at what alumni are up to, but to be frank I have no idea what I'm doing. Overall I'm looking for advice and or recommendations for schools to apply to. If there is anything missing in my profile that I should try to address before I graduate. Thanks in advance.
  7. Hi all! I'm in the process of applying for graduate schools (in both the US and Canada) and was hoping for realistic feedback so that I can manage my expectations. I think I'm a relatively strong applicant but a good reality check can always be helpful! Undergrad Institution: McGill University Undergrad Major: BSc Joint Biology and Mathematics GPA: 3.80 Relevant Courses: Math: Calc I (A), Calc II (A), Calc III (B+), Linear Algebra (A), Analysis I (A-) and II (A), differential equations (A), probability (B+), statistics (with R) (B+), stochastics (S/U'd), linear regression (A) and mathematical statistics (in progress) Biology: two semesters of intro bio (both As), two semesters of genetics (both A's), quantitative biology (A), multiple neuroscience courses Computer Science: Introductory programming in Python (A), Introduction to Computer Science in Java (B+) GRE General: V/Q/A: 164/169/5.5 Programs Applying MS: Boston University, University of Michigan, McGill University, University of Toronto Programs Applying PhD: University of Washington, New York University Research Experience: Summer grant-funded research and poster presentation in bioengineering department of my university, two years in quantitative physiology lab with one published paper (not 1st author) Teaching Experience: TA for General Chemistry 1-2, Organic Chemistry 1-2 and Intro computer science Employment: Online tutor for web-based company (~2 years, still employed), four month remote internship as laboratory assistant in Cusco (not sure if worth mentioning) I financed my degree on my own so I know I'm lacking a bit in extracurricular/leadership activities but I'm hoping my grades and research experience help me out a bit, please let me know if I'm shooting too high as I do have time to apply to other MS programs!
  8. 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.
  9. MS Biostatistics student looking for advice! Undergrad: top 30 LACs -- Statistics, Data Science (summa) Grad: MS Biostatistics Ivy League (not Harvard) Type of Student: International female GRE General Test: Q:170 V: 160 W: 5.0 Applying to: Biostatistics PhD Research Experience: Right now, projects on survival analysis (both applied and methodological) with a senior researcher -- not sure about potential publications! During undergrads, did summer research at a well-known cancer hospital and an institute for applied maths, and 2 year research at school. Letters of Recommendation: Two faculties with whom I'm doing/planning to do research with at grad school; one might be from profs teaching classes or undergrad studies who knows me very well Grad coursework: Same core coursework as PhD students -- using Casella and Berger for Probability and Inference. Have the option of taking the qualifying exam after 1st year (this coming June) with PhD students Publications: one conference paper on machine learning/applied maths from undergrads summer research. one coming up on using nonparametric tests for an applied project. Co 1st author for the former. Plan to apply: UPenn, BU, Columbia, Yale and maybe Harvard -- I want to stay in the northeast, New England preferably Can someone give me advice on the my school list? After my PhD I might go back to Asia where people care a lot about prestige and brand name of the school, rather than dissertation advisors. I realize this list is ambitious and would appreciate if someone can recommend some "safe" schools. Many thanks!
  10. Undergrad Institution: California Public University (Top Cal State) Major(s): Economics - Quantitative Analysis Minor(s): Statistics GPA: 3.958 Type of Student: Domestic Asian Female GRE General Test: (Have not taken yet) Programs Applying: Biostatistics/ Statistics PhD or Master’s Programs Research Interests: I am interested in Biostatistics research, possibly clinical research Research Experience: Do not have any professional research experience but will be completing a senior project which is a research project. I also was on a chem research team my freshman year, involved with the analysis part. Awards/Honors/Recognitions: Dean’s List, Top Biochemistry student freshman year Pertinent Activities or Jobs: Intern at KPMG as Risk Advisory Intern, Intern at Government Accountability Office, Intern at a startup. President of an academic club on campus. Letters of Recommendation: Manager at GAO, Stats and Econ Professor Related Coursework: Calc I-III (A), Linear Algebra (A-), Stats I-II (A), Statistical Computing in R (A), Programming for Econ (A), Applied Multivariate Statistics (A), Econometrics and Advanced Econometrics (A) , Marketing Analytics and Business Intelligence (A), Have also taken Bio/Chem classes (pertinent to Biostats?), Intermediate Microeconomics I-II (A) Future Coursework: Intro to Stats and Probability(calc based), Probability for Economic Decision making, Some more stats classes Applying: UC Denver Biostats, UC Davis (MS, PhD) for Stats and Biostats, U of Michigan (Bridge, PhD), UIUC (MS), UCSB (Masters and PhD), Rice (PhD) Notes: I switched from Biochem to Econ my freshman year. Concerns: Don’t have much research experience, but I have significant work experience as well as leadership roles Have not taken Real Analysis, probably will not be able to this year I want to know where I stand with my background. I know I haven’t taken the most math classes, but for a good amount of schools I pass the prerequisites. Funding is something that is important to me. I also want to know what other programs I should be looking at. I really appreciate any help. Thank you!
  11. Background: International student Female Bachelor's in Statistics with hons: 3.5 gpa( converted from Percentage) from tier 1 public university Masters in Statistics: 9.6 cgpa on a scale of 10 from a tier 2 private university with 10 in calculas, algebra, linear models, Design of Experiments, Biostatistics, multivariate analysis, Demography,Statistical Inference. Research experience: 1.Did a thesis project for final semester applying mathematical model to demographic rates. 2.Worked as a research assistant for 8 months at a government organisation but not very relevant experience or publication from it. I've graduated first in class in my master's program and have been awarded a national scholarship based on academic merit. Currently working as a Statistical analyst. GRE: not taking( applying to programs not requiring GRE. LORs: Three from my professors including the professor who was my project guide. I'm thinking of applying to PhD Biostatistics/ Statistics programs. My whatsoever little research experience is related to Biostatistics and it interests me the most. The programs I've selected so far are among the top 10 programs in Biostatistics Kindly suggest some schools which are not very ambitious and some safety schools for PhD Statistics. Thank you.
  12. I am about to be a junior this Fall and currently have a 2.6 GPA right now. I also don't go to a very popular college and it's located in the city. I have low grades and I am thinking about either getting into a masters program for applied statistics or maybe applied math. However, I might have no chance because I got a few C grades in my early math classes and I had to withdraw from Calculus 1 twice. I am also interested in economics and I have a B and B- in the first two economics classes so far. I understand that I screwed up bad but I am thinking about changing my life around. I have a total of 5 w grades and I am thinking about trying to at least get into a masters program for higher education as that I am thinking about pursuing a career in data science or possibly a consulting/financial field like quantitative analysis. I have a total of 5 w grades on my transcript so far and I don't want to end up a failure. I just need brutal honesty. I am currently about to be a junior this Fall and if it's not possible for me to get into a master's program, what are some possible career choices for me? What else can I do? I don't have internships yet but I am looking for some experience in the field so that I can get accepted later possibly. Are online master's a good choice because I was just thinking about that. I also graduate in two years so does anyone have some advice for me?
  13. From: India Background Undergraduate Institute- Top 3 for Math in the country Major- Math Minor - Physics Grades- 9.5/10 Relevant courses(with grades): Analysis 1,2,3(10 in all); Algebra 1,2,3(9,10,8); Probability(10); Calculus(10); Differential equations(10); Complex Analysis(10); Topology(7); Stochastic Processes 1,2(10 in both); Optimisation(10); Game theory(9) + Physics courses(overall physics courses 9.4/10) Masters: Top1 institute for statistics Overall percentage-82 Coursework(with percentage): Regression(62); Statistical Inference(84); Linear algebra and linear model(77); Analysis1(95); Probability(90) Currently taking- Analysis 2, Measure theoretic probability, Optimisation, Multivariate Analysis, Large Sample Methods Courses to be taken - Martingale theory, Functional analysis, Time series analysis, Large Deviations theory, Brownian motion and Diffusions, Weak convergence and Empirical processes, Percolation theory, Advanced functional analysis Projects: No research projects - only reading projects in 1. fourier series 2. mixing times Gre- not taken Toefl- not taken Applying for- Phd Statistics(focusing on probability) Suggest some schools and also any advice is welcome.
  14. Applying for PhD in statistics/biostatistics after working in industry for a few years as a Data Scientist - would appreciate any thoughts, feedback, or advice on programs below given profile/research interests. Undergrad Institution: US Top-5 in Statistics Majors: Statistics, Applied Math GPA: 3.91 Type of Student: International Male Math Courses (All A's): Real Analysis, Complex Analysis, Linear Algebra 1/2, Abstract Algebra, Numerical Analysis, Differential Equations, Calculus 1/2/3, Discrete Math Statistics Courses (All A's): Stochastic Processes, Time Series, Experimental Design, Linear Modelling, Data Science 1/2, Probability Theory, Statistical Computation Computer Science (All A's): Algorithms, Machine Learning, Deep Learning, Databases GRE: 168 Q | 163 V | 5.5 W Research Experience: 2 years in applied statistics (3rd author publication in lower-tier journal - did most of the coding), 1 year in sociology (no publications - mostly database management) Work Experience: 3 years as Data Scientist at large tech company Recommendation Letters: 2 from research advisors (strong letters), 1 from professor with multiple classes and strong performance (mediocre letter) Coding Experience: Python (expert), R (experienced) Research Interests: Causal inference, applications to social sciences (specifically education/public policy), applications to public health policy Programs Considering: UC Berkeley Stats PhD Harvard Stats PhD CMU Stats PhD UCLA Stats PhD UC Santa Barbara Stats PhD Harvard Biostats PhD Penn Biostats PhD Brown Biostats PhD MIT Social & Engineering Systems PhD NYU Data Science PhD Are there programs here which don't sound like a great fit with my interests and profile, or any not here which could be a fit? I recognize my list is a top-heavy, but I'm satisfied at my current industry job and would go back to school only for a relatively well-regarded program, with the end goal of tenure-track professor at a R1.
  15. Hi everyone! I posted in Waiting it Out, but thought I would give it a shot here as well I am anxiously awaiting any kind of response from both McMaster and University of Western Ontario regarding admissions to the master of sciences in statistics program. I applied in January, and it is now June and have not heard back from either school. Has anyone heard back? Either an acceptance, wait list or rejection? I am very frustrated at this point and would love to hear other applicants thoughts/journeys for a statistics masters! If anyone was admitted to either program, would you mind sharing your GPA or any work experience that helped boost your application? Any info is appreciated, and thanks in advance!
  16. Hi everyone, I am anxiously awaiting any kind of response from both McMaster and University of Western Ontario regarding admissions to the master of sciences in statistics program. I applied in January and have not heard back from either school. Has anyone heard back? Either an acceptance, wait list or rejection? I am very frustrated at this point and would love to hear other applicants thoughts/journeys for a statistics masters!
  17. Undergraduate Institution:Top 3 in math in India Program: B.Sc Hons. Major:Math and Physics Grade: 9.5/10 Type :International Asian Male Courses with grades: Analysis 1(10),2(10),3(10); Complex Analysis(10);Probability(10),Algebra 1(9),2(10),3(8);Calculus(10), Differential equations(10) ,topology(7),optimization(10), Game theory(9), Stochastic processes 1(10), 2(10) Masters Institution: Top stats program in India Major: Statistics with probability specialisation Percentage:84%(At time of application) Math courses with percentages: Analysis 1(95), Probability theory(90), Measure theoretic probability(90), Analysis 2(90), Optimisation(90) Stat courses: Statistical Inference (84), regression(62), Linear algebra and linear models (77) Courses I'll take next semester before the applications: Functional Analysis, Martingale theory, Time Series Analysis GRE(general): 169 Quant, 150 verbal GRE(Math)-Cancelled due to covid Research Project- None (have done some reading projects) LOR: Expecting 2 decent recommendations and 1 strong Programs applying: Phd Math focusing on Probability (Would also like to work on interdisciplinary fields with emphasis on probability if possible) School: Please recommend the range of school I should look for.
  18. Hi, I graduated with a bachelor of technology degree in Electronics from VIT Vellore, India in 2016 and have been working in statistical modelling/predictive analytics related profiles since then. I took various mathematics electives in college and enjoyed learning about different branches, and their applications in industry. I enjoy working on lot of versatile projects but over time, I realized that I am not learning anything in depth. Online courses related to statistics touch topics in a superficial way (no offence) and I would want to study some topics in depth, and pursue research. hence I am interested in applying for masters (thesis based) in statistics/PhD in statistics, starting fall 2022. Interest area - Missing data and methods of imputation, Parametric Methods BTech GPA: 7.92/10 GRE: 165Q, 159V, 4 AW Relevant Courses: Probability and Random Processes (calculus based) - S: Department topper for the course, also worked at TA with a professor in this course Multivariable calculus and differential equations - B Differential and Difference Equations - A Complex Variables and PDE - B Information Theory and Coding - B Applied Numerical Methods - B Numerical Analysis - B As you can see, my grades are average. Back in college I was not planning to study further and did not do much to improve GPA, focused more on only the courses I really liked. Research: - One research internship at a medical devices private firm for 4-5 months post college. It was in their R&D wing, worked on applications of statistics in diagnostic imaging. Not published. Projects: - Plenty of projects related to statistical methods, mostly around building parametric models. Some in traditional ML methods (Not Deep Learning). All done while in industry. None published. Other skills: Python, SQL, R, DBMS,SAS, Implementing models using Python. Remarks: Currently working in the same role. Realistically, I would not be getting a direct PhD (partially or fully funded) because of lack of solid background and no research work. Ques 1 - I'd like to get some input on my decision to start with MS in statistics with thesis work. I am not interested in Business Analytics/Data science programs as I looked at their courses and I have already self-studied most of it during my industry stint, it won't add much. I eventually plan to moving to a PhD in the same (unless I realize I am pathetic at it, then I could try for industry jobs). Ques 2 - I have put together a list, where I have looked into schools' research and their faculty profiles. I liked some good ones but they are out of reach, like UoW. Please suggest some schools accordingly too: My list so far is A - TAMU, Ohio State, UNC chapel hill, NCSU; M - UTD, ASU, Oregon State, Oklahoma State; Safe - Univ of Kentucky Lexington, University of Houston, University of Nebraska-Lincoln Its not a pretty profile but there are all kinds of people in the world, some of us wake up late but we try. I tried asking this ques in other places and got bashed for some reason. Thanks.
  19. Hello all, April 15 is the deadline to decide where I'll be going for my Master's in Stats! I'm posting here to get a better idea of where I should go. Here are my options: UChicago, Duke, UNC-Chapel Hill, UW-Madison, and ETH Zurich. Worth noting is that UW-Madison is free, although money isn't really a concern for me. As of now, I'd say I'm definitely leaning UChicago based on its prestige and the strength of its master's program. While I'm not that interested at the moment in pursuing a PhD following my Master's, I suppose leaving that door open can't hurt and that there's a lot of good in learning more theory at a place like Chicago. It also seems that there are plenty of opportunities for application-based work in their consulting experience, thesis, and electives at the TTIC. Is there any reason to consider the others over Chicago? In addition, I am still waiting to hear from U of Washington, which would be attractive to me if I do get in. So if you have any thoughts on them, please leave them here as well. Again, money isn't too big of a factor, but just so you know... UChicago and Duke are around the same price (47k/year) with scholarships I've been offered, UNC is about 30k, UW-Madison is free like I said, ETH Zurich is free (aside from the astronomical cost of living in Zurich), and no idea about UW yet. Thanks for any feedback!
  20. Thanks for reading this. I will be attending a Top 3 biostat master program next fall, and I want to seek for advice on how to become a competitive applicant for phd program in stat/biostat 2 years later, especially as an international student. FYI, I graduated from a top flagship state university with a major in statistics&computer science. I also have a minor in math but most math course I took are not proof-based and I only took one elementary analysis class (A+ grade). I also have done several research projects but do not have any publications. Specifically, I want to know given my background, should I prioritize taking more advanced proof math/analysis/probability class, or focusing more on doing research and possibly making some publications during my master study?
  21. I have been admitted to the statistics departments at both Harvard and Berkeley. I applied to 24 schools, so I've also been accepted to virtually all of the top 20 stats programs, excluding Stanford. My academic interests are pretty broad, but I'd like my research to be more theoretical and in the realm of probability or machine learning/deep learning, if possible. I'm also not sure if I will try to go into academia or into a research team at Google, Microsoft, Facebook, etc. I am mainly considering these two because Berkeley is so good at ML, but Harvard is a better fit in every other way (culture, location, etc.). Any advice would be appreciated! I am also happy to provide any more information.
  22. I am currently a senior DS at a FAANG company but my passion lies in academia. I have 2 publications, 3.5 GPA from large top 20 public school in Statistics, but my GRE general and subject test dates were cancelled last year due to COVID (I took them over 5 years ago and got 99% in GRE Quant, 85% in GRE Verbal, and 73% on math subject test). I applied to 12 top 30 ranked programs. Perhaps my concerns are premature but so far, I have only been admitted to one lower ranked program. The Berkeley faculty I interviewed with gave me the feedback that my coursework could be stronger (ie. Real Analysis and upper level Linear Algebra). In any other year, I would be grateful to get into any program, but I wonder if my lack of GRE scores and applicable coursework kept me out of top programs. As I want to be employable in the professorship job market after completing my phd program, I wonder if it would be worthwhile for me to reapply next round (taking the suggested courses, taking GREs, and I have a publication expected in the summer) instead of taking my one offer. Grateful for any thoughts and advice -- thanks! (and sorry if this is not supposed to be posted here 😕 )
  23. Hello everyone! My name is Vic (they/them) and I’m attempting to find a statistics and methods workshop to keep myself busy. I understand YouTube has plenty of informative videos but I find that I learn better when I’m interacting with the lecturer and other students in the class. If you have any suggestions please let me know!
  24. Dear all, I am an international applicant (from India) to the PhD program in Statistics/Biostatistics for Fall 2021 session. A little background about me: I completed my undergraduate in 2015, majoring in statistics with minor in mathematics and economics and my masters in statistics in 2017, both with US equivalent GPA of 4.0. Both my undergrad and masters universities are quite reputed (not ISI) and I believe I have decent mathematical preparation. After that, till now I have been working as a biostatistician at a pharmaceutical company. Along with my job, I have been involved in some academic research projects(not full time though). One of my research project is a collaboration work with professors from Yale biostatistics, Boston University statistics and Tel Aviv University statistics. Now I was asked by the professor at Yale to apply to the PhD program at Yale and I received recommendation letters from all other research collaborators and one of my master's professor. Yes, I am of course most interested in the Yale program because the work that I am doing is new and can be extended further into my doctoral research (perhaps) Although I have been involved in several research projects and presented talks or posters at international conferences about these projects, I have not been to get any publication as of yet (on the verge of submitting one and organizing for another submission currently). However, my GRE score is a bit on the low side 151V/163Q/4.5AWA and due to the pandemic, I could not retake the test. So, I was wondering how important GRE scores are for PhD applications? Now I know that the professor from Yale is not in the admissions committee, though I received an LOR from the same professor. Will my scores lead to automatic rejection? Particularly since the Ivy leagues are very selective in all respect. Thanks in advance for your replies
  25. I really need some solid advice on my SOP. I don't really have anyone to review the essay, so it would be a big help. TIA One summer break, as I was sitting in my room watching my country’s election coverage, I realized that the coverage lacked any substantive information. As an avid follower of international politics, I expected the networks to cover information on policy proposals, the future impact of those policies, and most importantly, polling data. However, the information presented was very trivial. This realization inspired me to scour through swathes of data from a wide range of sources and try to understand it and interpret it to come to a meaningful result. As I was going through this process of collection and interpretation, I realized that I loved it, and as I began looking into issues I felt they had a deep impact on my country’s development but received very little statistical research. Issues such as floods, earthquakes, and landslides were highly relevant, and social issues such as discriminatory practices received very little attention. So, I wanted to do something that could help prevent such disasters and bring those neglected social issues to light. Even though I was pursuing an engineering degree, I felt that my true potential lied in the Statistics field, and thus, decided to pursue a Master’s degree in Statistics. With a keen interest in Science and Mathematics, I always wanted to pursue a career in a STEM field, and I was fortunate enough to secure a merit-based scholarship from the Government of YYY to study Aerospace Engineering. During my undergraduate years, I strengthened my mathematics foundation, where I studied topics such as Advanced Calculus, Ordinary Differential Equations, Linear Algebra, Probability, and Statistics. I feel the mathematical courses that I studied have adequately prepared me for further graduate studies in statistics. The experiences I had during my undergraduate years have a profound effect on my life and career goals. My initial exposure to inferential statistics was during a small class project, “Aircraft Systems and Instruments”, where I collected data regarding aircraft crashes in the past few years in my country, XXX; and tried to find a correlation between them. Even though it was a small scale project, I was proud of the work that I had done. While studying engineering, I was further able to understand the power of statistical science. I learned about the use of statistics for risk assessments and quality control. In addition, I gained knowledge about the use of predictive analysis for satellite collision and avoidance systems and predicting the trajectory of space debris and meteors. While going back and forth between X country and Y country, I experienced the effects of disasters such as floods, cyclones, landslides, earthquakes, and other severe effects of climate change. And I felt that climate models could have been formed using concrete ground data, which could have been utilized to predict the effects of climate change and provide forewarning to the people in affected areas. Similarly, the massive problem of caste and gender discrimination pertaining to all of South Asia can be brought to light with proper statistical research. Keeping these experiences in mind, I aim to dive deeper into such vital issues during my graduate program, primarily by focusing on Bayesian statistics and computational statistics. I see statistics as a field of science that can overcome various scientific constraints and provide effective results. In my few weeks interning at AAA Airlines, I mostly worked at the data collection division under maintenance and engineering. During the internship, I learned a lot about data classification on an industrial scale and the real-life application of the data. The work mostly comprised recommending the maintenance engineers the need for periodic checks and replacement of parts based on the provided data. In line with my preparatory work for graduate studies, I took a “Data Science with Python Specialization” course through Coursera to further my knowledge in the emerging field of data science. Here, I got an introduction to machine learning, data mining, social network analysis, and data visualization using Python. Besides Python programming, I have programming experience in simulation software ANSYS, MATLAB, SQL, and C++, which I feel will be an asset during my graduate studies. As the world continuously becomes more data-centric, I feel that my limited knowledge of statistics will inhibit my ability to further my goals, and the arrival and haphazard management of the COVID-19 crisis has further ignited my thirst for statistical knowledge. In this data-centric world, high-level decisions are being made and will be made based on complex models, and I want to be in the center of such a decision-making process. I intend to work professionally in my country’s federal government and aid the government in various developmental works through data analysis based on advanced statistical methodologies and algorithms learned during the MS program. The MS degree in Statistics at the University of XXX will provide me with a platform to realize my goals and enhance my statistical skill set. Your program offers rigorous coursework and provides a wide range of research and training opportunities. I would be able to work with leading scholars and academics having a wide range of interests and perform real-world data analysis and research. With a multicultural environment and vibrant outlook, I feel that the University of XXX will be an ideal environment for me to pursue a Master’s Degree. To conclude, with my strong mathematical background and passion for statistical research, I believe I am ready to pursue a graduate degree in Statistics.
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