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Found 322 results

  1. 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
  2. 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.
  3. 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!
  4. 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?
  5. 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....
  6. 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.
  7. 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.
  8. 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.
  9. 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!
  10. 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!
  11. 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!
  12. 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?
  13. 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.)
  14. 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.
  15. 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
  16. 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!
  17. 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!
  18. Hi all, I'm a senior undergrad in the US graduating in the spring. I'm applying to PhD programs in statistics for fall 2020. I posted my profile recently and got great feedback, and I was wondering about a few more things: 1. I changed the list of schools I'm applying to, do they seem reasonable? I wanted to apply to more reach schools to give myself a better chance of getting into one, while also applying to enough lower ranked schools to not feel worried about getting into zero schools. 2. If I'm okay with doing a master's instead of a phd(in preparation for a phd), in general will it hurt me to apply for the phd programs? I.e. are there schools where you would get rejected outright(not even offered a master's) if you applied for the phd program but where you be accepted had you only applied for the master's? Undergrad Institution: Large public university ranked top 20 in math by US news Major(s): Applied Mathematics GPA: 3.89 GRE General Test: Q: 166 (89%) V: 165 (96%) W: 4.0 (57%) Math Subject Test: (probably won't take) Programs Applying: Statistics PhD/M.S Research Experience: Did a project related to Dynamical Systems with an applied math professor, and this summer have been doing a project with a statistics professor that I'll continue into the fall semester. Letters of Recommendation: Two from the professors I did projects with. The applied math professor will probably write an at least ok letter and I think the stats prof will be able to write a strong one. I'm going to ask a physics prof I took quantum mechanics with for the last letter because I did very well and I thought he liked me. Grades: Mathematics: Calc III(took in hs and it stayed on my transcript :///) (B), Linear Algebra and Differential Equations(honors and proof based) (A), Multi-Variable Calculus(honors and proof based) (A), "Applied Mathematical Analysis" which was a mixture of harder calc III and some complex analysis(honors) (A), Intro. to PDEs (B), Analysis I, II (A, A), Intro. to Measure Theory and Integration (A-), Intro. to Probability Theory(proof based) (B), Modern Algebra I, II (A, A), Numerical Linear Algebra (B+), Intro. to Mathematical Optimization (A), Intro. to Combinatorics (A) Computer Science: Intro. to programming (A), Data structures (A) Physics: 3 intro classes (A,A,A) a lab course (A), quantum mechanics (A), thermodynamics (A), classical mechanics (A), electrodynamics (A) Additional courses I will have taken before applying: Numerical Analysis, Stochastic Processes Schools I'm thinking about applying to:(For statistics phd unless otherwise indicated) "Safety"(not really of course): Iowa State, Madison, Illinois UC, Purdue, John Hopkins(applied math/statistics) Reach: Chicago, Columbia, U Washington, CMU, U Penn Any suggestions/feedback would be great! Thanks
  19. Hello! I am applying for statistics M.Sc programs. Would anyone be willing to look over my statement of purpose? If you are, please PM me!
  20. 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 !
  21. Having read the pinned post on research statements, I am still feeling uneasy about indicating potential advisers in my statement of purpose. The conventional wisdom in just about any other field seems to be that you should reach out to and engage in a dialogue with potential advisers before writing your statement of purpose . Is that really not the case in Statistics? I've tried emailing a few professors whose research called out to me, but I haven't had a response. I'm wondering if I need to write more compelling emails, or if this just is not an approach that works in Stats. So far, only a few of the programs I'm applying to ask you to specifically indicate who you'd like to work with - should I do it anyway for the rest? Is it risky if I say that I'd be interested in working with someone and it turns out that person isn't taking grad students currently? It feels like a difficult balancing act: I want to write with enough specificity to demonstrate maturity in the subject, yet I don't want to pigeonhole myself. Thank you!
  22. I am very interested in pursuing biostatistics PhD for this coming year (2020). I realize I have a low gpa score but have a strong research record/work experience to compensate. I would really appreciate honest feedback about my chances for graduate school this coming year given that I can get very strong LORs. Undergrad Institution: Top 10 LAC Major: Computer Science and Statistics GPA: 3.56 Student: Domestic POC, female Courses: Intro to Stat Modeling (A-), Intro Computer Science I (B+), Multivariable Calculus (A-), Intermediate Statistics (A-), Intro Computer Science II (B+), Linear Algebra (B-), Probability (B), Spatial Statistics (B+), Data Structures and Algorithms I (A-), Databases (A-), Theoretical Statistics (B+), Computer Systems (B+), Networks & Cryptography (A+), Data Structures and Algorithms II (B), Advanced Data Analysis (B+), Machine Learning (A-), Mobile Computing (B+). GRE: 161Q, 161 V, 4.5 Writing Applying to: QBS PhD Program at Dartmouth Ohio State University Drexel University George Washington University Rutgers Boston University UMASS University of Pittsburg UNC Chapel Hill Virginia Commonwealth University University of Maryland Vanderbilt University Emory University Brown University University of Pennsylvania
  23. Hey all! I'm looking for advice on where to apply, and an idea of where I'd get into for Fall 2020. I’m looking for schools that also have a PhD program in case I decide to keep going after Master's. I know my grades are not the highest and my GRE isn’t the best either, but I’m hoping I still have a chance. Thanks for your help! Undergrad Institution: Big state school Major(s): Statistics & Math Minor(s): n/a GPA: 3.758 Type of Student: Domestic white female GRE General Test: Q: 159 (70%) V: 153 (60%) W: 4.5 (81%) (Taking again soon, hoping to bring Q to 80%) GRE Subject Test in Mathematics: M: N/a TOEFL Score: N/a Programs Applying: MS in Biostatistics Research Experience: Did a Summer institute in biostatistics (SIBS) Program Awards/Honors/Recognitions: STEM Scholarship, deans list (all semesters but 1), university scholarship, math honor society, scholars program Pertinent Activities or Jobs: Math grader Letters of Recommendation: Professor for two of my stat courses (knows me well), instructor from SIBS (worked on research project together), mentor from STEM scholarship (knows me extremely well, but not in stat). Math/Statistics Grades: Calc I (AP), Calc II (B+), Vector Calc (A), Statistical Methods I and II (A, A), Linear Algebra (B+), Probability (B), Math Stat (B), Intro to Experimental Design (A), Transition to Adv. Math (A), Vector Analysis (A), Algebraic Structures (C) Currently taking: Theory of Statistical Inference, Computing in Statistics, Big Data Analytics, Analysis, and Ordinary Differential Equations (Also have 2 transfer courses in biostat from SIBS program both with A's) Any Miscellaneous Points that Might Help: Graduating a year early, almost all math and stat classes are 500-level with lots of theory Applying to Where: Duke Colorado - Denver UNC Boston (MS or MA) Emory Tulane Brown Probably some other (pls help)
  24. I am very interested in pursuing biostatistics PhD for this coming year (2020). I realize I have a low gpa score but have a strong research record/work experience to compensate. I would really appreciate honest feedback about my chances for graduate school this coming year given that I can get very strong LORs. Undergrad Institution: Top 10 LAC Major: Computer Science and Statistics GPA: 3.56 Student: Domestic POC, female Courses: Intro to Stat Modeling (A-), Intro Computer Science I (B+), Multivariable Calculus (A-), Intermediate Statistics (A-), Intro Computer Science II (B+), Linear Algebra (B-), Probability (B), Spatial Statistics (B+), Data Structures and Algorithms I (A-), Databases (A-), Theoretical Statistics (B+), Computer Systems (B+), Networks & Cryptography (A+), Data Structures and Algorithms II (B), Advanced Data Analysis (B+), Machine Learning (A-), Mobile Computing (B+). GRE: 161Q, 161 V, 4.5 Writing Research/Work Experience: Currently work as a Data Analyst at Columbia University Medical Center (a year), with having previously worked at IBM Watson Health as a Data Scientist (a year and a half). I have two research publications and have been working on multiple manuscripts and abstracts for conferences. I also participated in the Biostatistics Program for Underrepresented Students at Columbia University two summers in college. Applying to: QBS PhD Program at Dartmouth Ohio State University Drexel University George Washington University Rutgers Boston University UMASS University of Pittsburg UNC Chapel Hill Virginia Commonwealth University University of Maryland Vanderbilt University Emory University Brown University University of Pennsylvania
  25. Hi all, I am not going to ask you guys to chance me, as I know the application cycle will be an uphill battle for me from a low GPA and non-traditional background. I majored in Economics at an Ivy League with minors in Math and Statistics. I didn't do so well in the Economics with a few C's, a few A's, and mostly B's,(major GPA ~ 3.1) while my Math (mostly A's with an occasional A-), Stat, and other STEM courses such as CompSci and Econometrics was around 3.75. My cumulative GPA including the 'general ed' courses was right below 3.40, with the lowest semester being the first semester of my third year. I finish both my senior semesters with a 3.9. It seems that my GPA progression is hyperbolic and concaved upwards over the semesters. I will have taken up to Real Analysis, scoring A-/A in my math courses from undergrad and graduate institutions. Now, I am enrolled in my final year in a statistics masters program at a mid tier state school (to be specific - mid tier for statistics) and will be expecting a final GPA between 3.8-4.0. I will also be completing a master's paper on the topic comparing multivariate time series models using foreign exchange data (not a publication in a journal). My interest lies in financial engineering and multivariate statistics. My GRE is V:160/Q:166/W:4 (I plan on retaking. Also I am taking the GRE Math subject to hopefully scoring between the 50th to 70th percentile. The higher the better but without the math major, I don't know how feasible it is.) I have around 1 year of work experience in finance and data analytics (business strategy) as I recently finished my undergrad. So my questions for PhD programs are: 1) Besides the big names such as Columbia, Princeton, Cornell, and Berkeley, where else offers such programs with respect to my interest in financial engineering and high dimensional statistics? I'd like to stay on the coasts. 2) Which schools are more reasonable to be set as target schools? 3) Is it worth my while to work towards a post-bac in math to compensate for the GPA and gain the necessary coursework? Any advice would be much appreciated.
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