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Found 329 results

  1. Hi All, I am looking at applying to a few statistics PhD programs, along with some applied math and others. Student Type: Domestic White Male Undergrad: Top 100 overall (US News Rankings) Major: Applied Mathematics (minors Comp. Sci. and Economics) GPA: 3.72 Coursework: Linear Algebra (A), Calc I/II/III (A-,B,A-), ODE (A), Discrete Math (B+), Analysis I/II (A-,A), Applied Probability (A), Math Stats (B-), Operations Research aka some optimization (A-), Applied Machine Learning (A), Econometrics (A-), Algorithms (B+), Artificial Intelligence (A-), Data Structures (A) Graduate: 20-30 range in both overall and graduate mathematics programs in US Major: Mathematics GPA: 4.0 Coursework: Real Analysis I/II, Complex Analysis, Algebra I, Differential Topology, Probability I/II, Stochastic Calculus I, PDE I, Multivariate Statistics, Linear Models (GLMs, Cochran's, Gauss-Markov, High-dim.), Advanced Statistical Modeling (theory of some machine learning stuff), I might take this semester: Statistical Estimation (Lehmann & Casella, Point Est.) -- I'm under the impression that stats PhD programs will want to teach you this themselves though? GRE: V: 162, Q: 168, A: 4.0 GRE Math Subject: 760 -- Was going to take again, but I'm not sure now with the current climate. Any one recommend retaking for a higher score? Research: Publications: Coauthor on 1 Comp. Sci. conference using some Bayesian methods (mid tier conference -- not NIPS/ICML/etc.), 1 top financial journal with some econometrics (Journal of Finance/Financial Economics/Financial and Quant. Analysis). Misc: Semester of pure math, 1 1/2 years as a full time research associate in the operations management division at a top 10 business school, summer intern at a top quant hedge fund/prop. trading. Letters of Recommendation: 1 letter writer who I published both papers above with. Applied mathematics professor working mostly in the area of stochastics and finance. Several others who I'll probably switch up depending on the program: 2 profs I did recent research with (comp. sci. and finance), 2 from math profs (probability and analysis courses). Research Interests: My interests are still somewhat broad (and will probably change some more), but I enjoy/am interested in: Statistics: high dim., inference, some bayesian stuff related to time series. Probability: Mostly stochastic analysis (SDEs and the likes), random matrices. I get the impression only a few stats departments have faculty in this area? Interdisciplinary: Financial econometrics, some machine learning theory (regression based models, graphical models), and genetics (though I'm quite new to this area). Schools: Since I will also be applying to some other programs in applied math, I'm trying to keep prospective stats programs down to about 4-6 of the best matches, while also trying to keep in mind the number of admits these programs give on average each year. Washington, Michigan, Columbia, North Carolina, (Wisconsin/Penn St./UCLA/Rice)? Many thanks in advance!
  2. Hi, I hope everyone is doing well and staying safe! I plan to apply to graduate statistics programs soon. I'm primarily interested in masters programs, as I don’t feel competitive/competent enough for a PhD. I would love if someone could help me understand where I stand and if my feeling is correct. I also am very nervous about the kinds of schools that are a viable, given my background. I‘d greatly appreciate any advice! Type of student: Rising 4th year domestic mixed male Undergraduate Institution: Large public, no grade inflation (USN top 20 statistics department) Undergraduate Major: Applied Math - Stat concentration, CS minor, honors (not sure if that means anything) GPA: Cumulative: 3.90, Major: 3.95 GRE: Haven't taken yet; estimate: ~169Q, ~163V, ~4.5W Relevant Courses: (all undergrad level unless specified; all A's, except B's in ODE's and databases) Math: calc 1-3, real analysis, linear algebra, ODE's, mathematical probability, numerical methods, combinatorics, dynamical systems Stat: intro stats, linear models, data mining (grad level), sample survey/experiment design, intro operations research, topological data analysis, statistical computing, databases (grad level) Computer Science: intro programming, intro DS&A, analysis of algorithms, computer organization, programming languages Letters: average, but maybe below average - didn’t form very strong connections with professors Research Experience: 1 year of statistical modelling with biomedical science application; 1 year of work with a CS professor on a project with statistical focus in deep learning; no publications Internships: (not sure if this is relevant) one SWE/AB testing internship at local startup; one ML/NLP internship at a large public, but also relatively unknown, IT company Misc Experience: one TA position for a senior level math class; a lot of eclectic self imposed machine learning projects For masters I plan on applying to: (in order of descending perceived chances?) Texas A&M University, UNC, UWisc, Columbia, UMich, Duke, CMU, UW, UChicago, Harvard, Berkeley, Stanford. I have no idea if I am competitive enough to apply to these school though. They all seem super competitive, so I will likely apply to more schools. A big worry I have is that many of the masters programs in statistics are targeted toward industry/data science, rather than preparing for research/PhD - so idk if it is even worth applying to them. I am also unsure whether I have enough rigorous statistics courses to apply to PhD programs. Would love any advice! Thank you! p.s. sorry if you saw this on reddit, I thought it would be valuable to get specialized advice from here
  3. Hi, I'm planning to apply for a PhD in Statistics this year for 2021 fall, I would really appreciate any advice. Research Interests : Haven't really decided yet, broadly over statistical learning and statistical theory Undergraduate Institution: Best known in Korea Major: Statistics GPA: Overall : 3.9/4.3 (3.79/4.0 converting A+ to 4.0 for 4.0 scale), Major: 4.14/4.3 (3.97/4.0) (Excluding grad-level courses) Type of Student: International Asian Male Relevant Classes: Math Courses - Differential and Integral Calculus 1,2 (A0/A+) - Linear Algebra 1,2 (A+/A0) - Introduction to Mathematical Analysis 1,2 (A+/A0) - Differential Equations (A+) - Modern Algebra (A+) - Real Analysis (B0) ( Is this critical? ) Stat Courses - Concepts and Applications in Probability (A+) - Mathematical Statistics 1,2 (A+/A0) - Regression Analysis (A+) - Statistical Computing (A+) - Sampling Design and Survey Practice (A0), Experimental Design (A-), Discrete Data Analysis (A0), Multivariate Data Analysis (A0), Bayesian Statistics (A+), Survival Data Analysis (A0), Computational Statistics (A0), Data Mining Methods (A+), Stochastic Processes (A-), Nonparametric Statistics(A+) - Grad-level courses: Theory of Statistics 1,2(A0/A0), Probability Theory 1 (B+, I definitely did above median; i heard the grade was deflated this semester), Applied Statistics (A+), Deep Learning (Stat Dept, A0), Other courses - Game Theory(Econ Dept, A+), Optimization Models (IE Dept, A+) I'm planning to take few more grad-level courses on computational statistics, statistical methods, spatial statistics next semester. Test Scores : GRE general : V 157 / Q 169 / A 4.0 GRE subject math : Planning to take this October, expecting (>90%) TOEFL : 114 (R30/L30/S28/W26) Research Experience: Not much, I started an undergrad lab intern this summer, participating in seminars, so no clear results. I hope I could get some results (even if subtle) next semester, but not expecting much. Work Experience: - Data Analyst Intern for 6 months at a Ad-Tech company for 6 months: Worked on building ML models, learned python and sql; I think it's related with the field of statistics and it really motivated me to pursue a phd; definitely going to write about it at my SOP. - Statistical Research Assistance at a Sociology Lab: Working on analyzing survey data. Since it's in a completely different field, I don't really think it will affect my admission. Honors: Received Presidential Scholarship for 8 semesters for undergrad LOR : One from s stat professor of my undergrad lab intern, one from a stat professor i took few courses from, one from my ex-supervisor from the intern at the Ad-Tech company (He's currently a math professor at a different university). Questions: 1. Do you think a B on Real Analysis will have a critical effect on my admission? I think I have enough knowledge on measure theory needed for statistics, but I kinda messed up on the exams, and my grades aren't looking good... Even worse since I got a B+ on grad-level Probability Theory. Does my profile look like I don't have enough mathematical background on real analysis? 2. Do you think intern experience at an IT company can have any effect on the admission? I've heard industrial experience don't really have any effect on the admission, especially for math and stat. I feel like the experience is important, since I learned a lot about ML theories and how to deal with real data; plus I'm getting a LOR (expecting it to be strong) from my previous supervisor. 3. Will having grad-level courses in advance positively affect my admission? I think I should've took more math classes rather than grad courses, but it's too late anyways. 4. Do you think getting admission to top-30-ish programs (up to Yale I guess? based on US News) seem possible with this profile? I'm seeing a lot of people around me with better grades, more research experience than me, and I'm kinda losing confidence everyday I think about it. Do you think I should apply to lower-ranked schools for safety?
  4. Hi all, I am currently considering doing a PhD in biostatistics. I have been doing a lot of research on PhD programs, but I am still having a difficult time knowing what schools are my reach/target. Target PhD: Wharton, Yale, Cornell (social statistics), UW-Madison, UCLA(social statistics), Brown... Overreaching? Undergraduate Institution: Top 20 private liberal art college (Think Oberlin, Colgate, Macalester...) Major: Economics and Statistics GPA: 3.97 Type of Student: International Asian Graduate Institution: N/A GRE Score: 158 Verbal 168 Q, 5 W - first try, might retake it to get 170 on Q Relevant Classes: The grades in my intro classes are terrible, but I did better in upper-level math classes. My college does not offer as many stats courses compared to other schools. Cal II (A), Linear Algebra (A), Number Theory (B+), Real Analysis (A), Abstract Algebra (A), Probability and Statistics 1 (A), Probability and Statistics 2 (A) Introductory data science (A-), Statistical Modeling (A), Experimental Design (A), Econometrics (A), Causal Inference (A), Machine Learning (A) Research Experience: None. I have a senior thesis in which I applied causal inference technique. I also have another independent research project in which I examined different machine learning techniques and applied them to a real problem. Work Experience: At school: I served as TA in many statistics classes. After graduation, I am working at a consulting firm where I can work with professional statisticians and use a lot of statistical techniques. Letters: Average - Above Average? I will get two from my school, one being my advisor and the other being my independent research project professor. Both graduated from top PhD programs. I will likely get another one from my job, who also will have a biostatistics PhD credential from a reputable university. Now that I have written out these, I feel like my schools are even less reachable mainly because I don't have as much research experience, nor do I have a Master degree. I hope I can use my 2 years working experience at my consulting firm to offset that. Thank you very much everyone!
  5. Background: Graduated in 2019 with double major in Math and Computer Science and then worked in finance industry for a year. Returning this fall for a masters in the computer science department (at my school most statistics is under computer science) and will focus on some combination of machine learning / inference. My areas of interest in statistics are bayesian inference, causal inference, theoretical machine learning, and theoretical statistics. I am also interested in applications to healthcare. I would like to evaluate my prospects for applying to PhD programs in the fall in Statistics (or Biostatistics) and Machine Learning, as well as to hear feedback. Undergraduate Institution: Top 3 School. I will be starting a Masters in Computer Science focusing on inference/statistics this year and will be applying to grad schools in the fall. Majors: Mathematics, Computer Science Minor: Chinese GPA: 3.6/4 Major GPA: 3.76/4 Type of Student: Domestic White Male Courses taken: Math: Differential Equations (A), Linear Algebra (A), Real Analysis (no official grades that semester), Complex Analysis (B), Abstract Algebra (A), Intro to Stochastic Processes (A), Discrete Math Seminar (A), Logic Seminar (B), Intro to Probability (A) CS: Programming Fundamentals (A), Intro to Algorithms (A), Intro to Machine Learning (A), Algorithms II (B), Graduate Machine Learning (A), Graduate Seminar Machine Learning (A), Graduate Theoretical CompSci Seminar (A), Computer Systems (B), Software Construction (C) Stats: Graduate Mathematical Statistics (A), Graduate Inference (B), will also be taking 4 more courses in the grad statistics curriculum this year. Science: Biology I (No Official Grades that semester), E&M Physics (No Official grades that semester), Quantum Physics I (B), Quantum Physics II (C), Classical Mechanics (A), Intro Chemistry (C) GRE General Test: Not taken yet - seems like it might not be necessary? But happy to take if can improve my chances. Research Experience: Spring 2015-Fall 2016: Machine learning research in the physics department at a different university applied to theoretical physics data, published in a physics journal. Fall 2020: I will be starting a 1-year Masters this fall and will be doing statistics or ml-focused research. Working Experience: Fall 2017: Teaching Assistant for Abstract Algebra I Summer 2018, Sumer 2019-Summer 2020: Intern and quantitative trading analyst at bank Letters of Recommendation: Could get one from past research advisor, one from current research advisor, past work supervisor, or academic advisor Currently considering schools: PhD: What are my prospects at applying to top PhD programs (I.e. MIT, Stanford, Berkeley, UW, UChicago,...)?. Questions: Based on my background, am I better suited to apply to Statistics/BioStatistics or Machine Learning PhD Programs? Do you generally apply to do research under a specific professor, or is this decided after acceptance? Would it be more valuable to do masters research under: A well-known quantitative finance professor (would likely do relatively applied Ml/stats related work on healthcare data) A faculty in inference who is less well known (would probably do more theoretical work, the research group's interests are related to but not exactly bayesian/causal inference) How big of a problem is it that I have no experience in my areas of interest outside of my classes? Should I reevaluate? I would love feedback from you all and I greatly appreciate your help!! Please let me know if there's anything I can elaborate on! Thank you so much!
  6. Hey everyone, I would appreciate a rundown of my profile and would love some advice/tips. Thanks. I'm entering from a mostly unrelated field. Undergrad Institution: Large State School Major(s): Criminal Justice/Criminology Minor(s): Mathematics (Post-bacc mostly) GPA: 3.5 (4.0 since start of Junior year) Type of Student: DWM, LGBT but I probably won't be mentioning that in my application. GRE General Test: I'm a very bad test-taker and will be retaking. Q: 157 (62%) V: 161(88%) W: 4.5 (80%) GRE Subject Test in Mathematics:n/a TOEFL Score:n/a Grad Institution: n/a Concentration: GPA: Programs Applying: Statistics/Biostatistics (Master's only). Research Experience: Unpublished firearm policy/casualty trends research conducted through R. My mentor on this project is an epidemiologist at my university and will be writing one of my letters of rec. I've also been listed as a contributor on a submitted-for-publishing epidemiology study. I also have one presentation at a conference under my belt. Nothing too exciting. Awards/Honors/Recognitions: Nothing outside of president's list. Pertinent Activities or Jobs: TA'd a Calculus course for economic/business majors. Also employed as a math tutor at my university. Letters of Recommendation: Two letters from math professors I know very well (including the one I TA'd for) and the previously mentioned epidemiologist. Math/Statistics Grades: Calculus 1-3 (A), Discrete Math (A), Linear Algebra (A), Intro to Statistics (A). I'm also taking Probability, Diff Eq, and a prerequisite course to Real Analysis this upcoming semester. Any Miscellaneous Points that Might Help: Without being too specific, a lot work I did in undergrad had ties to public-health in minority populations. My main interest is using/developing statistical methods to better study aspects of healthcare, especially those that are more related to SES issues. I don't know how programs would view this since my background isn't strictly in Math/Biology/Statistics. Also, if I fail to increase my GRE Quant to 163+ before the deadline, how badly do you think my chances will be impacted? Applying to Where: (All Master's) (You're welcome to add suggestions, although I'd prefer to not be on the West Coast.) University of Florida University of Georgia University of South Carolina University of North Carolina-Chapel Hill University of Iowa University of Minnesota University of Michigan Duke University Emory University Thank you!
  7. Howdy, I am a rising senior and am planning to apply for PhD and masters programs in Biostatistics for Fall 2021. However, I currently do not know where I stand and whether the schools/programs I have chosen are realistic. I would love to go straight into a PhD program, but I am unsure of if this is feasible and would love feedback! Undergraduate Institution: Top 60 LACs Majors: Biomathematics Minor: Urban and Community Health, Music GPA: 3.80/4.0 Major GPA: 3.76/4.0 Type of Student: Domestic White Male Courses taken: Math: Math Modeling w/ Biological Applications (A), Differential Equations (A-), Mathematical Modeling (A), Calculus III (B), Linear Algebra (A-), Agent-Based Modeling (B+) CS: Programming Fundamentals (A) Stats: Applied Statistics (A), Applied Regression (A), Biostatistics (A) Science: Biology I (B), Biology II (B+), Conservation Biology (A), Evolution (A) GRE General Test: 321/340 (V:160, Q:161, W:4.5) Research Experience: Spring 2018 - Spring 2019: Ornithology Research (including Summer Fellowship), presented at three conferences Spring 2018 - Present: Biomathematics Research on Florida Plant Species (including Summer Fellowship), presented at two conferences, published a paper Fall 2018 - Summer 2019: Frog Research at local zoo, volunteer research assistantship Summer 2019 - Present: Biostatistics Internship at local Health Science Center (includes both Summers) Summer 2019 - Present: Plant Distribution Research, presented at one conference Fall 2019 - Present: Data Analysis for Art History Professor, research assistantship Spring 2020 - Present: Agent-Based Modeling for Florida Plant Species Spring 2020 - Present: Economic Simulations Research I hope to have two more papers published by the time I graduate, but they will not be ready in time to place on my application. Working Experience: Spring 2017 - Present: Teaching Assistant for Math Modeling w/ Biological Applications Fall 2018 - Present: Teaching Assistant for Applied Calculus I also tutor off-campus for middle school students and am a freelance musician. Letters of Recommendation: One from biomathematics professor/research advisor, one from statistics professor/research advisor, one from an epidemiologist/internship advisor. Currently considering schools: Masters: University of Tennessee, University of North Carolina, and Vanderbilt University PhD: University of Mississippi and Vanderbilt University I would love feedback from you all and I greatly appreciate your help!!
  8. Hi, I correlated all my study variables, and some of the demographic variables, with each other, to see if there were any significant associations. I found significant correlations between some study variables with demographic variables. For example, let's say I analyzed which type of candy participants like eating the most; and the amount of candy XY eaten correlated with participant's educational status. This would seem like a "spurious" association, as in there would be no obvious explanation why participant's education should be associated to how much of candy XY they eat. My questions: 1) Is it common to to this sort of preliminary correlational analyses to explore associations between variables? 2) Should I report significant correlations, even if they are not part of my study questions/hypotheses? 3) If yes, should I mention these significant correlations as well in my discussion? Or can I simply report them in my results part, and them not mention them anymore in the discussion? Thank you in advance !
  9. Hi all, I look for the advices about my profile for applying Ph.D. in Statistics in Fall 2021. I am so nervous about the incoming application season since my GRE score in Verbal part is pretty low. I took it many times but my score didn't go up. Currently, I am master student majoring in Statistics in the US University. Type of Student: International Asian Male Applying to: Statistics PhD Undergrad Institution: Top 5 public university in my country Undergraduate Major: Mathematical Statistics Undergraduate GPA: 3.8 Graduate Institution: University in the US (Ranked between 11 - 20, according to the USNew) Graduate GPA: Currently 4.00 Graduate Major: Statistics Work Experience: I worked as a Data Scientist for 1 year GRE General Test: Q167 V147 W3.0 I also have a question here that should I retake it? GRE Mathematics: Not taken Undergraduate Relevant courses: Math: Calc I (A), Calc II (A), Calc III (A), Calc IV (A), Fundamental Concepts of Mathematics (Learning about how the proof) (A), Linear Algebra (A), Differential Equation (A), Introduction to Numerical Analysis (Pass; I audited this course) Stats: Intro to Regression (A), Design of Experiment (A), Categorical Data Analysis (A), Introduction to Multivariate Analysis (A), Probability Theory (B+), Statistical Inference (A), Introduction to Stochastic Process (A), Time Series Analysis (A), Statistical Quality Control (B+), Statistical Simulation (A) Others: Data Mining (A), Data Science Practicum (A), Operation Research (A), Research Methodology (B+) ** Calc IV at my university is studying about the Sequence and Sequences and series of functions, uniform convergence, tests for convergence of improper integrals, vector-valued functions of several variables and surface integrals. Graduate Relevant courses: Stats: So far, I have taken Regression, Multivariate Analysis, Probability Theory, Statistical Inference, Design of Experiment and Bayesian Modelling (All of them are Master's level) I think that I will take the Regression, Statistics Inference (Ph.D levels) and some Computational Statistics course. Research Experience: I have done a research with the Statistics Professor for 8 months about the EM-Algorithm. Recommendation Letters: 1 of them will be from my professor who I work with and the other 2 will be from the professors who I took his course at get A/A+. Planning on Applying to: Actually, I wish for Standford, UCBerkely, UMich, North Carolina State, Colorado State. However, I'm open to all. I just wonder that what should be some good safety university for me? Thank you in advance for your suggestions
  10. I am a graduate student in my second year and would like to apply for PhD programs in Statistics. I am uncertain about how successful my applications will be as I don't have a Stats background, but a couple of professors at my grad school told me I should give it a shot. Undergrad Institution: International private institution Undergraduate Major: Electronics and Communication Engineering Undergraduate GPA: 3.57 Graduate Institution: Private school in Southern California Graduate GPA: 3.85 Graduate Major: Business Analytics Type of Student: International Female Work Experience: 3 years as a Business Analyst GRE General Test: Q:168 V: 170 W: 4.0 GRE Mathematics: Not taken Applying to: Statistics PhD Research Experience: doing quantitative research with a professor in the Marketing department. It is application oriented and will involve time series analysis to solve a use case Letters of Recommendation: No one well-known, but can get 3 decent ones from school (one with the Professor I am doing research for) and corporate Math/Other Relevant Grades: Undergrad (International)- Engineering Mathematics I (A), Engineering Mathematics II (A), Engineering Mathematics III (B), Engineering Mathematics IV (C) Statistics/Other Relevant Grades: Grad (USA)- Statistical Computing and Data Visualization (A-), Marketing Analytics (A), Data Driven Decision Making (A), Business Analytics (A-), Fraud Analytics (A), Text Analytics and NLP (A), Applied Modern Statistical Learning Methods (A) Planning on Applying to: Dream schools: UC-Berkely, UCLA, University of Washington, CMU, UPenn, Cornell, Duke What would be some good safety schools? Is it worth applying to a PhD program in Statistics with my profile? Which schools can I target? Thank you for your help.
  11. Hi everyone! First time posting here. I was looking for some feedback on my profile and what kind of universities I should be targeting. I'm not looking for a PhD, want to gain better knowledge of Data Science to improve my career prospects. Looking for universities in both US and UK. Degree: B.E. (Hons.), Electronics & Instrumentation Engineering, BITS Pilani Goa (Tier 1 university in India), CGPA: 7.8/10 GRE General: 336 (Q 170, V 166, AWA 4.5) Had taken the TOEFL in 2018, will need to take it again this year. Score last time around: 112 (W:29 R:29 L:29 S:25) Grades in Relevant courses, converted to US equivalents: Mathematics - I (Linear Algebra & Geometry): A, Probability & Statistics: B, Mathematics - II (Calculus): B+, Mathematics-III (calculus): B- Work Experience: 3 years so far as a data scientist (2 years in an analytics consulting firm, 1 year at a startup working with a sports franchise - this is the area I would like to proceed with). Another year before I go. Research Experience: None LOR: a professor I had a project under in college, my manager at the consulting firm and my current boss (CEO of the startup). I'm open to consider any programs in the US or the UK. Thanks!
  12. I do not know if it is early to post in this forum, but I thought I would get some suggestions before starting the process. Undergrad: Big State School ranked around 150 Major: Mathematics, with Minor in Computer Science GPA: 4.0 (By the end of Junior Year) Student Type: International Male Undergraduate Courses: Calculus Series, Into Linear Algebra, Differential Equations, Proofs and Logic, Discrete Mathematics, Undergraduate Real Analysis Series, Intro to Programming, Object Oriented Programming, Data Structures, Data Science in Python (Mostly Sickit Learn packages implementation), Data Visualization in R, Database System. Undergrad/Grad Hybrid Courses: Mathematical Statistics I, Mathematical Statistics II, Elementary Number Theory, Analytic Number Theory, Abstract Algebra I am planning on taking graduate level real analysis series (including measure theory), advanced probability series (measure theoretic), Topology, Advanced Linear Algebra, Multiplicative Number Theory, and Algorithms in my senior year. GRE General: Will take this summer Math GRE: Haven't decided yet Research: I have worked in analytic number theory since last August, found a small new result last month. I improved the error term of an important formula (Peparing the work to submit for publication). I am currently working on probabilistic number theory, but do not know if I will get any mentionable result. I got a prestigious summer fellowship of Fields Institute for this summer. I was initially supposed work on probabilistic number theory at University of Toronto for this summer as a part of fellowship, but the program has moved online because of Covid-19. I do not know how effective this online research program would be, but I will work very hard to get the best out of the program. I was also accepted to present a poster at a conference this summer, but the conference got moved to next year due to Covid-19. Letters of Recommendation: My primary advisor (number theorist; he wrote good letter that helped me land fellowship), hoping to get a letter from the professor who will become my research supervisor this summer; my computer science professor, and real analysis professor have written good letters for me in the past, so will ask for them as well depending on the program. Programs Applying to: Statistics PhD Interests: Bayesian Statistics?? (Haven't narrowed down the interest, but something that is more mathematically inclined). Considering to Apply to: Need suggestions about what should I target. Notes: What level of schools should I consider targeting to? Do I have a decent chance at top level schools to spend time preparing for subject GRE? I think I tick boxes for average to good level graduate programs, but I am not sure about top programs. As I am an international student and did not have any AP credits, I spent first two years taking 4 calculus classes, linear algebra, discrete mathematics, proofs and logic, which mostly covered what I already knew. So, I had to wait until my Junior year to take advanced mathematics classes. Also because we have a small department, I do not have options to take a lot of advanced courses. So, I neither have a strong mathematics nor statistics background. My undergraduate degree has mostly been a little of this and a little of that. But my advisor says that I have done a decent amount of work in number theory for an undergraduate student. As I still have about 7-8 months and a good summer research opportunity before applying, what should I do to make my application strong? And what level of schools should I have in my mind when I am preparing for my application? Do I have decent shot at schools like University of Michigan Ann Arbor or North Carolina Chapel Hill?
  13. Hey I have looked around here a bit but have not seen the answer... It is a long the same lines as those asking about science recs for ASHA. I am looking at what stats class to take and want to take the easiest one to fill the requirement. I am planning on taking my pre-recs at UW Madison and am looking at Psych 210 Statistics for Psychology. Has anyone taken it? Does anyone know if ASHA will accept it? The more obvious choice is 301 Intro to Statistical Methods but the pre-rec for that is having satisfied the Quantative Reasoning A requirement and I am an adult returning student and I have no idea if I have met that requirement....
  14. I had mediocre to poor performance during my undergraduate career due to family/financial issues. As a result, my major GPA in mathematics was around a 2.5 (I do not have to exact number as it is not listed on my transcript) and my cumulative GPA was around a 2.8. Fortunately, my institution offers a certificate program (akin to something like non-degree studies) to essentially re-take graduate level versions of undergraduate courses, but I am wondering if that would be the best course of action as I am also considering the Math GRE subject since my performance was so poor. Is it totally unrealistic for me to entertain applying to any masters degree program (after this SARS-CoV-2 outbreak is over of course) if I undertake one or both of these options and do well? Thanks for any advice.
  15. Hi! I am trying to decide between the current offers for Stats PhD I have from Purdue, Minnesota, Ohio State and Univ of Toronto (Math Finance track in Statistics dept). I am interested in the areas of Machine Learning and high dimensional statistics, although I am open to explore new areas and then decide. Other than UoT where supervisors are already assigned, I have the flexibility to choose my supervisor in the other 3 places. In UoT, I have the chance to work at the interface of machine learning & finance which I find appealing. My questions are: 1. Which would be a better choice if I want a career in industry and which would be more suited for academia? 2. Among the US universities, is there any significant difference in the reputation of the 3 places? How close does the best of the 3 come to UoT in terms of research and future prospects? It would be really helpful if someone could suggest well-reputed faculty members or someone doing good research in the areas of ML and high dimensional statistics at Purdue, Minnesota & OSU. Note: Due to the COVID-19 issues, I am considering deferment to next fall. While the US universities have given me the option to do so, there has been no such assurance from UoT so far.
  16. Hi all! I will be applying for to MS Statistics/Biostatistics programs in US and canada.My end goal is to finish my masters and go for a PhD in Statistics. Undegrad Institution : University of Delhi (tier 2 college) Major : Economics GPA : 7.12/10 (3.6 US equivalent) Releveant Courses : Math/Statistics : Math Econ I (7) ,Math Econ II (8) , Statistics (7), Introductory Econometrics (8), Applied Econometrics (10) All grades are out of 10, the two math courses covered some linear algebra and the rest was multivariable calculus but did not have vector calculus stuff like green's theorem. The statistics course was calculus based and had random variables, hypo testing, clt and similar stuff. Econometrics was mostly regression stuff. Graduate Institution : Indian Statistical Institute Major : Quantitative Economics ( MS in QE) Grade : 86/100 (This is only one semester, I rank 4 in a batch of 23.) Relevant Courses : Math Methods (95), Statistics (95), Game Theory (91), Probability Theory (66) All grades are out of 100.Math course had good amount of linear algebra, decent amount of real analysis and a lot of optimization topics like KKT. Statistics was taught from Casella & Berger, was very mathematical had things like cramer-rao bound, cramer woldt device, likelihood ratio test, NP lemma etc, Prob Theory was from the stat department and I couldn't do well in it because Real Analysis was a prerequisite which I had not studied, the course had convergence concepts(almost surely,distribution etc) and markov chains. Relevant courses from this semester are Econometrics I, Theory Of Mechanism Design( not sure how relevant but it is a mathematical course) and Game Theory -II When the time to apply comes I will have had a course in Real Analysis(Analysis-I from the stat dept) and I am pretty sure I'll get an 80+ in it and I will also have had and additional course in Econometrics, one in Sample Survey and and one in Time Series, in my last semester I will also take either Measure Theory or Analysis - II depending on my interest, I cannot take these now or in the next semester as the Institute doesn't allow too many courses from other dept. in one semester. General GRE : Quant(165), Verbal(164) GRE Mathematics Subject Test : Not given yet. The things that I worry about are that my UG institute wasn't really the best in the country, it wasn't a bad school but just wasn't amongst the top colleges, my GPA in UG is also not fabulous however I think it is still better in the relevant courses. Will bad grade in prob theory be a significant factor? I am also planning to give the GRE Math by studying for it over the summer, I think I should be able to manage 70+ percentile on this, will this add significant value for top schools because if not then I could intern over the summer and make good money. LOR : One will be from my game theory and Mechanism Design professor who is a PhD in industrial engineering, rest all will be from economists though should be good. My dream programs are Stanford MS Statistics, U of Chicago Stats, Harvard Biostats, CMU,U of Washington. For canada I know that U of toronto does not take international students so I was thinking about U of waterloo and UBC. Can you guys tell me about my chances at these schools and also the schools that I should actually apply to . Also what else can I do to improve my chances of getting into the best programs, and should I do a not stats relevant internship in the summer or give the GRE Math, sorry for too many questions.
  17. Someone helps me! I am so hesitating! I will list pros and cons of these two programs and plz vote! 1. Columbia University Teachers College Applied Statistics pro: It's location is the best. CU is my dream school. con: TC is so independent and I am afraid of being questioned as a student of CU. Also this program is often being criticized. 2. UPenn GSE SMART(Statistics, Measurement, Assessment, and Research Technology) pro: GSE is better than TC. con: Location is not as good as NY(for me). Please share your opinions!
  18. Someone helps me! I am so hesitating! I will list pros and cons of these two programs and plz vote! 1. Columbia University Teachers College Applied Statistics pro: It's location is the best. CU is my dream school. con: TC is so independent and I am afraid of being questioned as a student of CU. Also this program is often being criticized. 2. UPenn GSE SMART(Statistics, Measurement, Assessment, and Research Technology) pro: GSE is better than TC. con: Location is not as good as NY(for me). Please share your opinions!
  19. Someone helps me! I am so hesitating! I will list pros and cons of these two programs and plz vote! 1. Columbia University Teachers College Applied Statistics pro: It's location is the best. CU is my dream school. con: TC is so independent and I am afraid of being questioned as a student of CU. Also this program is often being criticized. 2. UPenn GSE SMART(Statistics, Measurement, Assessment, and Research Technology) pro: GSE is better than TC. con: Location is not as good as NY(for me). Please share your opinions!
  20. I have been accepted to PhD programs for the upcoming Fall at the University of Florida (UF) and the Iowa State University (ISU). -> UF has a small program with younger faculty--most of them are recent graduates from ivy schools--while ISU has one of the largest Statistics department in the US. ->UF is ranked #40 this year and ISU is tied at #20 -> Both places have research that interests me -> UF has a better reputation as a research university in general Please help me decide on picking the school for myself. What factors should I consider before making a decision? Are there any current graduate students or alum from these schools who can give some pros and cons on the schools?
  21. I know that internal fellowships tend not to matter much beyond the period of time in which you have them. I've been offered two rather different fellowships, however, and I'm trying to determine if the difference between them is substantive or not. The first is UNC's Royster Fellowship, which comes with about a $6,000 stipend increase. It seems rather prestigious and selective, with the fancy name, university-wide competition, and inclusion into the "Royster Society of Fellows," with lots of different networking and professional development opportunities. My guess is that all of this apparent prestige will only matter while I'm at that particular university, if at all. So, Question 1: Do people outside of UNC (in academia or industry) know about (or be impressed by) this so-called "Society of Fellows," or is it just fancy window dressing on a (more competitive) funding award? The above fellowship also includes two years without duties--one during my first year of intense coursework and the other in my fifth year during my dissertation work. (So from years 2-4 I would work as a TA/RA, but with a guarantee of the same level of funding as in years 1 and 5.) Question 2: As someone going into a STEM field, how much help is a fifth year fellowship? Everyone else in the program is already guaranteed TA/RA funding for 5 years. Would not having work duties be instrumental to finishing up my research in my fifth year, or just a convenience? (I'm sure that this will depend on the progress of my research and how early I start, but any input would still be appreciated.) Finally, my other big offer is a rather bland-sounding college-level "Dean's Fellowship" which comes with a larger funding increase--around $13,000 more than my initial offer from that department. Only the first year has no teaching duties, however--for years 2-5 I'll have to work as a TA/RA but for the same increased stipend level guaranteed. While both departments are undoubtedly trying to recruit me, my gut feeling based on the fellowships is that I would be more valued at UNC. It seems as though their STOR department has had only one other Royster fellow in the past five years, whereas I get the sense that the other department's fellowship is much more common and less of a "big deal". Question 3: Is this thinking completely illogical? Does the difference between the level of fellowships each department nominated me for give any signal as to how valued I would be by the faculty and department? Does getting a more competitive fellowship inherently mean I would be a "bigger fish" in that program, or should I just take things at face value? (Admittedly, trying to gauge how desirable I am as a candidate after I've been accepted might be a bit of a waste of time, but I'm self-aware enough to know that feeling valued by a given department is important for my productivity, self-esteem, and long-term academic success.) I would greatly appreciate anyone's thoughts on any of these questions. (Or people to tell me to quit being silly and obsessing over trivial differences, if it turns out that the answers don't really matter.)
  22. Undergrad institution: big U.S. state school with decent math department Majors: Double Degree with BS in Math and BA in Econ GPA: 4.0 / 4.0 (both major and overall) Type of student: International (White male) Courses taken: Math: Basic: Calc I - III (A/A/A), Linear Algebra (A), Ordinary Differential Equations (A) Advanced: Abstract Linear Algebra (A), Abstract Algebra I - II (A/A), Mathematical Analysis I - II (A/A), Numerical Analysis (A), Intro to Partial Differential Equations (A), General Topology (A) Stats: Probability and Statistics (A), Mathematical Statistics (A), Stochastic Processes (graduate credit: A) Programming: College courses: CS Java course (A), CS Python course (A) Coursera online courses: C++ course, Algorithms and Data Structures, Machine Learning: Supervised/Unsupervised + intro to Hadoop/MapReduce/Spark Courses will take: Real Analysis (graduate credit), Mathematical Economics (graduate credit), Calculus of Variations (graduate credit), Differential Geometry Recommenders: Math professors, well-known in their respective areas, with whom I have good personal contacts Research experience: This is my weakest point, since I have not been able to do any particularly notable research as an undergrad. I applied and got accepted to REU this summer but could not attend due to family reasons. At the department level, I tried doing research with one of my professors in statistics, but he left soon after, so the paper was never finished. Work experience: Financial Analyst Intern (Summer 2018), Data Manager Intern (Summer 2019) Awards: Economics and Math Department Scholarships, President's Honor Roll for every semester GRE General: 157 (V), 167 (Q), 4.5 (AWA) GRE Math: Taking this fall School list: Need advice on where to apply. One of my friends suggested that I should apply to schools where my professors got their PhD's. But other than that I don't even know which tier to aim. My biggest concern is the lack of research experience. Masters is not an option, since I just can't afford it right now + I am on my national government grant.
  23. I am not MFE concentration so I don't know how good is Applied Operational Researches concentration. UW is known for their stats(correct?), but I have heard few comments on this program. My main concern is job opportunities as I intend to work in the Stats after graduation
  24. Hi everyone, I just received the PhD offer from CMU stats department, and I am so happy with that. However, now I am facing a difficult decision between choosing to stay at University of Toronto for my PhD (where I did my undergrad) or go to CMU for a new adventure. My current research interest is more about: 1. Applied Bayesian inferential methods. 2. Statistical Computations. 3. Machine learning and Data Science. And my future plan is to find a faculty position in statistics. The pros for UofT: 1. I am an international student, so staying at uoft makes it more possible for me to get the PR card in Canada, while the PR card in US is a bit impossible... 2. I did my undergraduate study at here, so I know the faculties at this university very well. And I have been matched with my preferred supervisors whom I have already worked with and felt good working with, while CMU currently did not match me with any supervisor yet. 3. There will be five years of full funding package which includes full-tuition plus 20k stipend per year for UofT, while CMU's offer only describe my full funding package for one year (full tuition + 3.1k stipend per month), and based on their student handbook it seems like the funding from CMU usually only lasts for four years... The pros for CMU: 1. Higher ranking in Statistics, especially in Machine learning and Data Science. 2. Based on the suggestions from my professors, if I want to continue my career in academia, it seems like it would be better for me to not go to the same place for both undergraduate and PhD... But I am not sure how important that factor is 3. Probably the winter at Petersburg will be more approachable than in Toronto... Could anyone give me some suggestion on how to make this choice? Any suggestions is appreciated! Thanks so much!
  25. Hi all, I'm planning on applying to statistics PhD programs for next cycle (entry in Fall 2021) and would love an honest assessment of my profile, with strengths and weaknesses, and recommendations on programs to apply. My interests broadly are statistical machine learning with applications to healthcare and social sciences! Undergrad Institution: Top LAC Majors: B.S. Mathematics and Economics GPA: 3.97/4.0 Type of Student: Domestic White Male GRE General Test: Q: 170V: 170W: 6.0GRE Subject Test in Mathematics: 760 (71%) - April 2019 Programs Applying: Statistics PhD Research Experience: In my job since graduating college I have been working on health economics and epidemiology studies, and have a number of co-authorships on publications (although not directly related to statistics). Hoping to move away from biostatistics even though it's more relevant to my current work experience (I am aware biostats and stats departments are very similar!). I also presented an economics research paper at a well known economics conference with my thesis advisor from school since we wrote a continuation of my thesis after I graduated. Awards/Honors/Recognitions: Summa cum laude, award for top economics student in graduating class. Pertinent Activities or Jobs: 1.5 years of research experience in health economics and epidemiology in my job. Letters of Recommendation: I have two math professors who know me well and said they would be happy to write me strong letters (both of them offered when I mentioned I was thinking of applying to PhD programs), one of them very well known in their field. The other is my thesis advisor from the economics department. None of them strictly from statistics department, but hopefully they are relevant! Coding Skills: R, Python Relevant Classes, Grades: All undergraduate level 😕 Mathematics: Statistics (A); Multivariable Calculus (A); Linear Algebra (A); Discrete Mathematics (A); Mathematical Modeling and Computation (A+); Data Mining and Machine Learning (A); Financial Calculus and Probability (A); Real Analysis I (A+); Real Analysis II (A); Abstract Algebra I (B+) Other Relevant: Introduction to Programming with C++ (A). Advanced Econometrics (A). Comments: 1. I think that my biggest weaknesses are my lack of graduate classes (I added a math major very late in my career at the recommendation of one of my letter writers from the math department) and while I have research experience in publications in a related field, none of it is directly statistics. Also, I took the math GRE after a year out from college and was definitely rusty - I feel like it's a respectable score but am unsure if it will help or hurt my application for those that don't explicitly require it (i.e. not Stanford!) Could you guys help me get some clarity on that? I know it's a hotly debated subject (pun intended) on this forum! 2. One recommender said I would have a solid shot at some top 10 programs but I am not feeling as confident - what do you guys think? I will definitely have a few "shoot for the stars" schools on my list that really align with my research interests of machine learning and social science applications (Berkeley, Harvard, Michigan) but I need to add some more realistic schools I think, unless you guys feel otherwise! Thanks you all so much for reading - I've learned a lot from going through this forum and would love your guys' input!
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