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Found 133 results

  1. Hey all, I am planning on applying to graduate school in statistics. Would you recommend taking the math subject test? Thank you
  2. Need some help, thought I'd make an account an ask...Do I have any chance of getting into a decent Stats PhD? I'm a junior attending an "elite" US institution (top 15), but don't have a solid GPA (3.54). I'm majoring in Stats and Economics, and my major GPA is around a 3.6. I've taken calculus and linear algebra, but have no advanced math classes, although I do plan on taking real analysis in the Fall. I have no research experience. I don't have a great relationship with any of my professors. ...All that said, how screwed am I? I literally never considered a PhD before this month, so I never bothered to research or do anything. At this point, I'm left coasting on my university's name, which I'm still not sure will get me anywhere. If anyone could chance me in general and recommend me schools that I could actually get into, I would be highly appreciative. My top two schools are Rice and UTAustin at this point, but I'm not sure I could get into either... Edit: Haven't taken the GRE yet, but I'm expecting a 90% percentile+ in the Quantitative section...I feel like the only thing I can do is standardized tests. I'll probably look into the Math GRE subject test as well and try to study over the summer...
  3. I'm new to this site so please forgive any breach in protocol. I am currently a math and physics double major at my undergrad institution, which has a small grad program, but I am not particularly interested in attending there. I plan on applying to phd programs in statistics, despite no research in mathematics, although I do have research experience in physics. I also was not able to take any graduate courses because of the double major. I have yet to take my GRE's, though I expect decent scores on general, and I am not sure whether I will take the subject. My gpa is a 3.88, a little higher for math, a little lower for physics. My letters should be really good, although none will come from statistics professors. My question is, is this an issue? Also, what schools would be attainable given the information provided, how many schools to apply to (ie; safety, target, reach). Thank you.
  4. I've narrowed down my final two choices for a PhD beginning Fall '17 to Johns Hopkins University's Department of Applied Mathematics and Statistics (School of Engineering) and Brown University's Department of Biostatistics (School of Public Health). I've been accepted at both. I'm interested in applied statistics (I have work experience in data science and an M.S. already), so biostatistics sounds like a natural fit. I'm curious about the reputation of the Brown program. It seems small but mighty! My concern is that by going to Brown, I'm throwing away the opportunity to rub shoulders with JHU Biostatistics (they rejected me), but I suspect it's better to like the department you're in rather than the department you're near. I haven't heard much about JHU AMS. Thanks in advance for your $0.02.
  5. Well, I promised in the other forum that if no one else did this I would. Follow the template below, and post your profiles / results. These posts have been indispensable for future applicants and are extremely helpful for prospective students that have no idea where they should apply / have a shot. Also note that TGC limits the time in which you can edit your post, so you may wish to post your results in your signatures so you can change it (if you haven't already heard back from everywhere / almost everywhere). Undergrad Institution: (School or type of school (such as Big state/Lib Arts/Ivy/Technical/Foreign (Country?)) Major(s): Minor(s): GPA: Type of Student: (Domestic/International (Country?), Male/Female?, Minority?) GRE General Test: Q: xxx (xx%) V: xxx (xx%) W: x.x (xx%) GRE Subject Test in Mathematics: M: xxx (xx%) TOEFL Score: (xx = Rxx/Lxx/Sxx/Wxx) (if applicable) Grad Institution: (school or type of school?) (if applicable) Concentration: GPA: Programs Applying: (Statistics/Operation Research/Biostatistics/Financial Math/etc.) Research Experience: (At your school or elsewhere? What field? How much time? Any publications or conference talks etc...) Awards/Honors/Recognitions: (Within your school or outside?) Pertinent Activities or Jobs: (Such as tutor, TA, etc...) Letters of Recommendation: (what kinds of professors? "well-known" in field? etc.) Any Miscellaneous Points that Might Help: (Such as connections, grad classes, etc...) Applying to Where: (Color use here is welcome) School - Program / Admitted/Rejected/Waitlisted/Pending on (date) / Accepted/Declined School - Program / Admitted/Rejected/Waitlisted/Pending on (date) / Accepted/Declined School - Program / Admitted/Rejected/Waitlisted/Pending on (date) / Accepted/Declined
  6. I am applying to Statistics PhD programs for the 2018 season. I have done a few practice tests on verbal and quant and thus past week I did my first essays. The argument essay I get, but the issue task is not up my alley at all. I would give myself right now a 2.5 on Issue and a 4 on Arguement. My verbal is around 160, and my quant is around 163 (trying to get it up to 165+). I am a native English speaker, and I have a research paper I am working on getting published as a writing sample. Does my AWA score really even matter? Do the separate scores (i.e. I-2.5, A-4) get reported or is there just the final score on the score reports sent to colleges?
  7. Hey everyone! I am wondering which one should I choose. Columbia University is a big name and it locates in NYC. However, I heard the reputation of their Statistics program is not that good in recent years. I really like University of Michigan, it has relatively small class size (about 30) and the school overall has a good reputation. But Quantitative Finance and Risk Management (QFRM) is a new program (opened in 2015) and its location is not as good as Columbia's. The key parameter I am considering is job placement. Thank you for your help!
  8. I've already considered about my decision for two days but I cannot figure out anything. I'm graduating with a statistics BS this spring, and I plan to become a data scientist after earning my master degree. NYU definitely has a better location, and the program is very good and popular. I believe it's easier for me to get a job if I choose nyu. However, Duke is a world-renowned school and the MSS program is also among the best nationally and internationally. I just don't which one to choose, and I have a strong feeling that the decision will affect my future...
  9. School: Large Public Research University (40-45 ranked math department - USnews ranking) Major: Mathematics, Computer Science Minor: Economics GPA (Cumulative): 3.81/4.00 (Math): 3.9 Mathematics Coursework: Calculus I,II,II (A-,B,A-), Discrete Math (Intro to proofs) (B+), Linear Algebra (Proof-Based) (A), Ordinary Differential Equations (A), Real Analysis I (A-), Real Analysis II (A), Abstract Algebra I (A-), Complex Analysis (A), Linear and Nonlinear Optimization (A), Financial Mathematics (pretty much just a course in stochastic calculus) (A), Numerical Analysis (next year), Partial Differential Equations (next year) Statistics/CS Coursework: Probability Theory (A), Statistical Theory (A), Graduate Machine Learning (A), Data Mining (A), Financial Econometrics (A), Time Series (next year) Math Courses with Ws (and then retook for A/A-): Calculus III, Abstract Algebra I, Probability Theory GRE Scores: 169Q, 165V, 4AW (I was going to apply this year, but decided to finish up my computer science degree by taking a 5th year, and add some more research to my profile) Letters: 2 from professors having done research, 1 from professor I took several classes with (opportunity to do research with next year too - see below) Research: -non-relevant to statistics (both in number theory): Semester Research Project, Summer REU -relevant: year long research opportunity (if I accept - see below) PhD Programs (preferred) : Chicago, Michigan, Harvard, CMU (joint machine learning - honestly, I never see anyone get admitted to this though), Berkeley, Wisconsin, Penn, Penn St, Duke, University of North Carolina, North Carolina State, Columbia, Cornell, Purdue, UCLA MS Programs: Harvard, Stanford, Chicago, CMU, Berkeley, Duke, Washington, UCLA (trying to keep this top heavy, since the consensus is that masters are easier to be admitted to) I have quite a bit of interest in machine learning, and would prefer going to a program that has some faculty doing research in this area, but I wouldn't say it is a deal breaker (i.e. if I was admitted to Chicago I'd go, regardless of the minimal research in ML). Some Questions: 1. I have four W's, three of which are in relevant mathematics classes (listed above). I was struggling financially at the time, father was laid off and not able to find steady work. During these periods, often of which were not given with much heads-up, I had to take on 40 - 60 hours of work and could just not keep pace will all of my courses. Figured it probably better to withdraw and retake, rather than take a C. How much weight will this have on my application? 2. Would it be more beneficial to complete a undergraduate thesis OR one year of statistics relevant research with a professor?
  10. Hi, I am Esther. My major is statistics and I hope I can enhance my programming and language skills via a master degree. Also, I hope to learn some data science knowledge. I am quite glad that I can receive AD from UCB, Umich, Duke and UIUC. i am now an actuarial analyst with ASA license and hope to find a analyst position (especially in actuarial firm) in US after completing my degree. I am not really sure which university should I choose. In my opinion, Umich and Duke are two years duration, so I would have more time to find an internship during summer term. However, UCB has better location but shorter time. All of them contain some data science courses. I am really appreciate any advice that anyone provide me.
  11. For those of you who are currently enrolled or have completed a PhD in math/stats/biostats how was your time split up during your first year between: Coursework Teaching Research Other(?) I know not every program is the same and that some students may have teaching duties waived so I am just trying to get a general sense of what to expect.
  12. In case you haven't seen this on your own or through Chris Blattman's blog post last week, Seeing Theory is a really neat learning resource for introductory statistical concepts. The site attempts to make statistical concepts more accessible through creating a visual learning format, allowing users to interact with visualization tools to get a better understanding. For some of the stats- and quant-averse folks in the IR/PP crowd, this could be super helpful. I know that in my own experience, getting a firm grasp of the geometric intuition underlying mathematical and statistical principles has been immensely beneficial in getting to the 'Aha!' moment where something really clicks.
  13. My undergraduate major is Mathematics and a minor in Economics, and my college offers three real stats classes (Mathematical Stat 1/2, Stats for Engineers/Scientists (applied calculus based stats). I know that Statistics undergraduate programs aren't that common (at least compared to math), and that I don't need a stats major/minor to get into grad school for stats. I would like to self-study a little more stats before I (hopefully) start atStats grad program in Fall 2018. For those of you with an undergraduate minor/major what classes did you take and what textbooks did you use? I have Wackerly Math Stat already. I am looking for textbook suggestions that are more undergraduate focused and do not require anything above Real Analysis I. I would like a Regressions book and a book on Bayesian Statistics for sure, and anything else that you think would be helpful.
  14. Hi- I have a background in Computer Engineering and seek an eventual PhD in Statistics. Knowing I lacked some of the math courses necessary for a PhD, I applied to PhD programs where you could be considered for the Master's program if not admitted to the PhD. I have been admitted to UCLA, UCSB, and University of Michigan for Master's, and am hoping to attend one which is going to prepare me best for continuing on to a PhD program. I know, for example, that Michigan's Applied Statistics Master's seems somewhat more catered to preparing students for industry, but I had also seen that a few of their students do in fact continue on to do a PhD. I was curious if anyone could provide insight on these programs and inform me of the program's reputation in addition to how focused each Master's is on preparing a student for industry versus continuing on to a PhD. Thanks
  15. Really struggling between this two school. Rice:1. Relatively small school and closer connections between alumnus and professors. 2. Larger choice in cross-disciplinary lectures NCSU: 1. Better Professors and better location for job opportunities (maybe?) 2. cons: seems change to summer program for one year since 2016 and have no idea about how is the program actually now and the summer lectures are taken online. Really need help! Thank the replies in advanced for you time and patience.
  16. Hello, Can people give me their opinions/ranking on any of the schools (Statistics PhD): UCLA, UF, Texas A&M I've been admitted into these schools, and I'm having hard time deciding... My opinion: UCLA -seems good for industry jobs (i.e. data science), since located in LA -course load seems heavy on machine learning (good) -expensive to live in though (apartment/food worries...) UF -course load seems to be more oriented toward traditional statistics (no machine learning courses) -I heard they're theoretical heavy (good) -located in my hometown (wouldn't have to worry about life stuff, i.e. cost of living, food, etc.) Texas A&M -I heard they're a very large department that does mostly applied stuff -I'm not that worried about the cult life thing Bio: -Undergraduate: UNC Chapel Hill, Graduating in May 2017 with Bachelors in Stats, Math -US Citizen -Hoping more for industry than academic job Thank you so much!
  17. I'm currently deciding between Penn State MAS program and the Cornell MPS program. Both will be a one year program because I did my undergrad at PSU. As a current Penn State undergraduate I'm leaning towards the staying here because I'm familiar with the area, the professors, have a job, research hook ups, ect However, I know Cornell has very good name recognition. My main goal is to go straight into industry. I looked over the post graduate survey for Cornell and was unimpressed with the average salary (70k) seeing as a few months ago I turned down a 63k a year job hoping to get accepted into graduate school. I'm not aware of any Penn State version of post graduate survey. The price tag is about 22k for Penn State and Cornell is 52k in tuition alone. I could probably afford Cornell without too many loans (coming out of undergrad I have no loans) but I feel that the average starting salary should be higher to justify the double price tag. I'm wondering if anyone has any insight into which program could be better for me. I'm an American and I know most of Cornell MPS students are chinese internationals so I'm wondering if that's bring the average salary down significantly and that for a domestic student, the salary prospects are much better. Thanks in advance for any help.
  18. Hi Guys, another School A or School B question here. This time it's UNC and NC State for a phd in statistics, perhaps the most diametrically opposed (in terms of theory vs applied) of the departments I applied to. As for me, my interests are not very set in stone. I enjoy machine learning and spatial stats, but I'm fairly open to most subjects in stats/probability. And my mind is not made up on industry vs academia, so I would prefer the school that keeps either option open. I would highly appreciate any input on my dilemma. Particularly on the question of which department is considered "more prestigious" as I keep getting ambiguous responses to this question (US news world vs other rankings, statistics vs probability professors, etc) (A&M is also an option, but I would need some major convincing to live in college station)
  19. Has anyone applied for MSc in Statistics/Biostatistics at UBC?? Checked with them two weeks ago, the secretary said they were still in the process of reviewing application ....
  20. Hi, If getting a job in companies like IBM,microsoft, amazon (basically tech) is the end goal of studying a program, which program is better? Thanks!
  21. Hi! I've been recently admitted to the University of Michigan applied masters in statistics program. I would like to know more about the reputation of the program. Are the classes hard/ is the program tough? Is the program worth the money? Do students who graduate from here have a better chance for a statistics PHD in the future? ( Since I know it is a program that focuses on sending students into the industry) Thank you!
  22. Hi guys, I am currently at junior at Cornell University, and last fall I changed majors from Astronomy to Operations Research and Information Engineering after 3 research jobs in astronomy/physics and realizing that the only part of physics I liked was the data science. I have taken Probability I & II and I am currently taking Statistical Data Mining and Stochastic Processes. I am now doing research for a professor in oceanography on measuring the change in chlorophyll at every point in the oceans. I have not been able to get really good advice on what I should do for graduate school. I want to work in applied statistics at research centers such as Pew, the UN, NASA etc. I think I'm leaning towards doing more social statistics research rather than now.. In Astronomy you had the option to work in theoretical (like string theory), more applied (like researching solar winds etc), or technological (like designing telescopes). Now I've been told that Statistics PhD programs are completely theoretical/methodological, whereas I was hoping to do a thesis on a more applied topic. So I guess my question is should I try to go for a PhD to then be able to get a higher position at a research center that requires PhD credentials so that I can finally do what I like doing? Or are there any programs that would let me do more applied statistics (that would be ideal) I should specify that I love my statistical data mining class, and I have been enjoying all my probability and statistics classes, but I enjoy applying what I have learned to data rather than coming up with new methods. Also I was told by a professor that getting a masters is worse than dropping out of a PhD program????
  23. I am trying to get a ballpark figure on acceptance rates to middle and lower tier (30-60 US news ranking) Statistics Ph.D. programs. I found data on acceptance rates on top 30 schools but not a lot on the middle tier programs. I am a female domestic applicant with 3.75ish Math GPA (state school), research experience, a possible undergraduate publication (if it gets accepted), and great rec letters. I am guessing from survey results and the limited information I found that my chance of getting acceptance with funding is around 20% on average for these schools. I want to apply to enough programs to get a 90%+ chance of at least one offer. I figure you could build a binomial model of the number of funded acceptances. I want to know if 20% is a good estimate of the probability of me getting into a middle or lower tier program with funding. Obviously the probability varies across colleges, and this won't be the best estimate. Some Example Colleges : Florida State, South Carolina, Baylor, Virginia Tech, Kansas State
  24. Good afternoon, everyone. Thank you for for being a great resource for future applicants like myself. Currently, I am gearing up to apply for the 2018 cycle in statistics and biostatistics masters programs. One topic I haven't seen touched on much through search was class size. How big are the classes at the top 15 schools? I understand we have epi students and non-biostat/stat students in some classes, but how big are the cohorts? Do they vary widely by school? Thanks, Future applicant
  25. Hi all, I'm a year 3 student from National University of Singapore (NUS), currently exchanging in UCSD. My primary major is quantitative finance. I also got double major in Statistics and minor in CS. I plan to pursue a master degree, but could not decide between master of Stats or financial engineering (or even industrial systems engineering). At this moment, I'm aiming at job in banking area (To be honest, I haven't got a VERY interested area yet, if watching drama does not count lol). I know that stats provides more opportunity while MFE is more specific, but could anyone give me some advice other than that, based on my information here? Plus: I am open to every kind of possibility because I'm really confused. Some of my basics are as follows: GPA: 3.78/4 (Converted from 4.73/5) 1 individual research project (Econometrics based. Not published.). Charted Financial Analyst (CFA) level I passed. Relavant courses: Math: Mathematical analysis I, II Linear algebra I, II Numerical analysis ODE Numerical PDE Mathematical finance Finance: Accounting Corporate finance Financial markets Investment instruments Stats: Probability Regression analysis and linear model R/SAS/SPSS programming Planning: Stochastic process Time-series CS: Data structure I, II Computer organization Language: Python, C++, Java, Matlab