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Found 15 results

  1. Some statistics: Undergrad: A current senior in top 50 public uni, double major on Biochemistry and International Relations Overall GPA: 3.1 Biochem GPA: 2.49 International Relations: 3.74 with departmental honor Research experience : 3, all related to international relations/political science Relevant Prerequisite: Calculus 1-3(3.0-3.2), STATS: Element of the statistical methods( the title of the class), currently learning python on Coursera. Plan to take linear algebra and matrix in my last year. Recently, I decided to pursue a master's degree in Data Science/Applied statistics/ Information systems. I am currently taking a stat class, which I found really interesting, which prompted me to switch my field of study. That being said, I did some researches and am now greatly discouraged and not sure if I should do this, especially after some programs said they will review the coursework in science to evaluate the applicant's potential (especially if the applicant do not have a degree in a similar field). I am now really worried about my Biochem grade being a drag. Is there any way to offset the negative impact of that? Provided that I do not have much space for taking more than 4 related mathematical/programming classes in my last year being a double major. I am also thinking of getting a master first in computational social science as a stepping stone and then dig more into the statistical program for the second master, which however will be time-consuming and a financial burden. Any advice will be appreciated. Thank you!
  2. Hi, Seeking advice/opinions on applications for Stat PhD courses in the US. I will be applying to start in Fall 2022. My profile: Nationality: Indian (undergrad in UK, IB Diploma in Singapore) Grade Scale: 1st - A+, 2:1 - A, 2:2 - B Undergraduate - BSc Economics (London School of Economics) with 2:1 Math/Stat Courses - Mathematical Methods(1st), Elementary Stat Theory(1st), Abstract Math( high 2:1), Operations Research(high 2:1), Econometrics(2:2) Postgraduate(Not sure if this is considered postgraduate) - Graduate Certificate in Theoretical Probability and Statistics from Open University (will complete in July 2021) - Im doing this as i have not taken stat courses to at least an intermediate level. Im hoping that this would also help with preparing GRE Math subject test. I have not yet taken GRE and I intend to take the GRE Math Subject test. LOR(have not got yet but expected): Average. Did not build good rapport with professors at undergrad but will do for the grad certificate. Relevant Work Experience: Worked in Credit Risk Advisory in the year since graduating and credit risk internship during the first summer of undergrad Other Relevant Experience - Econometrics Student Lecturer, Quantitative Economics research project I would like to apply for Statistics PhD programs at Washington, UChicago, UMich, U Wisconsin Madison, JHU, Rutgers, UPenn, CMU, BU, Georgia Tech etc I am also open to doing a Biostat PhD ( i do not intend on doing my PhD research in financial statistics) I know i do not have an undergrad math/stat major, but im attempting to improve that situation through the grad cert in theoretical probability and statistics. How do i stand amongst the competition? Would i stand a better chance completing an MA or MS then applying to a PhD program? I have until Dec 2021 to add education/work experience/ qualifications. How can i improve my profile ? Appreciate your advice and thanks for your time!­čÖé­čÖĆ
  3. Hello all. It's my first time posting here and I apologize if it's not the right forum for such a post. Would anyone here happen to know of the pros & cons of USC's M.S. in Statistics? I mean no offense, but if I may be blunt, some friends have shared that some USC's master programmes are "cash cows". I couldn't find much candid commentary on USC's M.S. in Statistics online and am hoping that stats grad students may be able to weigh in. Subjective opinions are okay Thanks for reading. USC = University of Southern California (in case the acronym USC is overloaded)
  4. Hello and thank you for your time reading this! So I have narrowed my acceptance down to two schools: Madison and Minnesota. I am from Wisconsin originally so I will considered in-state at both schools. I completed my undergrad at Wisconsin and I am currently unsure about continuing on to a PhD later. I am leaning towards getting a job in industry, probably in the health care sector. Additionally, I currently have no loans but by graduation, will only have a few thousand left in the bank. Wisconsin would be my choice as it is fully funded and a better program. But before April 15th, I may be offered a spot in an, NSF funded, Data Science in Multi-Messenger Astrophysics at Minnesota. I was told I have real chance of getting in but right now, this is tentative. If not accepted, I will probably go to Wisconsin. This is a year long position with a more generous $34,000 stipend along with fully paid fees and health insurance. Additionally, it offers mentoring, internship opportunity's, team research projects and potentially funded travel to conferences. This seems to have huge potential but if it doesn't pan out, I could be paying a lot more money. UW-Madison Pro's: Two years of guaranteed funding. A much better school (16th vs 24th nationally). Madison seems to be an echelon above Minnesota. I know the dept, have a good reputation, and have made connections already. Con's: I will be returning to the same school as undergrad and I want to try something new. TA position is only $20,000 for 9 months. Not as easy to stand out amoungst so many great students. UM- Twin Cities Pro's: I have a better chance of standing out, publishing research and attaining higher highs. I could chain this early success into another research/lab position in my second year. Bigger city means more opportunity and a chance to start anew. Con's: More expensive (10k overall); if i fail to get a second year position, it will be $35,000 more in cost. A worse department and worse institution overall. High risk, this position could be far worse then I am imaging. In closing, I'd love your opinion on where to go, how significant the difference in program rankings is and how highly I should think of this training program? Sincerely, Mr. Plumbo
  5. Hey! I'm currently a 4th year undergrad majoring in statistics at UC Berkeley. Right now, my plan is to apply for a master's in statistics or data science within the next 2-4 years, as I'm planning on doing data science work for at least a year before applying. My question, though, has to do with my grades this semester--in particular, due to the coronavirus, my school has given us the option to either take our classes pass/fail or we can request a letter grade. They are pushing hard for us to do pass/fail, but I'm not sure this is the best option for someone like me who hopes to go to grad school in the future. My main concern is that I was hoping to improve my major GPA this semester, as I'm finishing my last 2 stats requirements. My major GPA is a 3.5 right now, and my overall GPA is 3.7 if that's important. So, I'm conflicted as to what to do... I feel like I should be able to take my school's advice and stick with pass/fail, but at the same time, I'm not sure how this would affect my grad school applications. I also do believe that as time goes on, my grades will matter less and less, but I could be wrong on this. Anyway, since I'm not applying right now and should be working for at least a year before applying, perhaps I just shouldn't stress about trying to get good letter grades and should just chill and do pass/fail? Still, it's an annoying decision to have to make, as I feel like I could probably do well in these classes despite the craziness going on in the world right now. Lastly, I understand grad school admissions committees will obviously understand that we are amidst a global pandemic and that therefore tons of other students will also have pass/fail grades this semester. But still, I'd hate to take my classes pass/fail if it seems good letter grades could really help me in my grad school pursuits. That's it... I'm just very conflicted. Thank you for any clarity you all can provide!
  6. 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.
  7. I received a mail from a faculty member requesting for a Skype interview. Can someone help me out with what kind of questions I am to expect from them? What are the things I need to look up at beforehand? This is the first interview I have received so I would much appreciate if ya'll could drop some tips. Thank you!!!
  8. Recently I got admission from University of Chicago and University of Washington (Seattle), both are statistics master programs. I hope to work in IT companies in my future career, such as FLAG. As far as I know, the stats program in Uchicago tends to be very theroretical, and it asks students to take 9 courses and a thesis in order to graduate, which is a pretty good program for those who want to pursue a Phd program after graduation. And if I want to be a data scientist, a Phd degree is much better than a master degree when seeking for a job. Also´╝îUChicago is well-known for many other subjects as well, which has a more wide reputation. But the computer science subject in UChicago is not its strong subject and if I want to be a data scientist in IT companies, I need to take more computer science courses as well since my major in math during BS. On the other hand, the stat program in UW only asks students to take courses and some of the courses have some projects. The university is in Seattle, where has a lot of IT companies, so it is convenient for me to find interns and jobs after graduation. And if I graduate from that university, the job I want would focus on software engineer /machine learning engineer /data analyst. And CS in UW is much better than that in Chicago, and if I want to solidify my computer science, I could take more courses there. I am really really confused about which to choose. Can anyone give me some advice on the program and the career development? Many thanks!!!
  9. Hi everyone: I recently got accepted to WUSTL AM Statistics program, and I'm struggling to find any discussion about the program. All that I've seen during my searches on this forum and google are some rate my chances threads. I assume it's because of the small size of the class plus the fact that statistics is still part of the Department of Mathematics in WUSTL. Just wondering if anyone can add some information on the lack of information issue. Here's a little bit of my background: graduated with BS in math/econ and statistics, worked in industry for two years as a data analyst (mainly writing machine learning analysis code. unsupervised, supervised, classification, nlp, etc.) After working in industry for a while I really feel that I want to do more advanced-level work. Anyways here are some info that I've been able to gather about the program: 1. 7 faculty, 13 phds, 10 masters students in total (part of the Math Department) 2. Required courses: 5, including: a series of two classes (two series to choose from, one 400 level on mathematical statistics and one 500+level that's more proof based. 400 series might be taught by postgrad lecturers; 500+ by faculty) one out of two classes (one 400 level and one 500+ level on linear models. I couldn't find any meaningful difference in course description. Both taught by faculty) two 400 level classes on bayesian and statistical computation. Both taught by faculty. 3. Optional thesis 4. Two year program assumed by a line that says 'two semesters (or 18 units)' in the description and the program requires 36 units to graduate. I do have three concerns for the program: 1. It seems like this program is a 'cash cow' since it says no financial support. Does this necessarily imply lower quality for and attention given to masters students? 2. Even though there's a full phd outcome page, there is no mentioning of masters outcome. 3. Some classes (including required) are 400 level. Does this necessarily mean they are undergraduate level courses, or just being 400 due to administrative reasons? Some supporting info: the phd program also requires the two 400 level classes on bayesian and statistical computation. Does anyone have any thoughts on the program? Or is there anything that can be inferred about the program based on the info that I found? Would really appreciate any help.
  10. Hey Guys! I know we have a lot of experienced members here who see these kind of posts very often. Can someone please have a look on my following scenario and recommend some programs/schools that seem reasonable for my profile? Please help me out here and feel free to be brutally honest!! Program of Interest: MS Statistics (smth more inclined towards applications especially in data analytics) Undergrad Institution: #218 National University US News & World Report (a US public school) Major: BS Mathematics, Minor: Economics CGPA: 4.00/4.00 (Last 60 hours) Type of Student: International, Male Relevant Coursework: Calc I (A+), Calc II-III(B), Linear Algebra (A), Mathematical Statistics I-II (A+, A), Real Analysis I (A-), Intro to Proofs (A+), Econometric (A), Data Analytics Tools (in Python) (A), DBMS (A), Foundation of Algebra I (DG) (Not taking again), In progress (SP 2020): Eco and Business Forecasting, BI, Data Mining, Numerical Analysis, Mathematical Computing GRE scores (This is where I completely sucked :( : V/Q/AW: 141/159/3.00) Relevant Experience: Peer Tutor in Math & Stat for over a year in our department's tutoring center Computational Skills: Intermediate knowledge in R, Python, and MySQL. Thank you for your time and patience.
  11. I recently graduated with a BS in a natural science and a minor in stats. I believe I have most of the prereqs needed for Statistics MS programs: I've taken Calc I and II, Linear Algebra, and 4 stats classes. Calc 3 seems like the only major prereq I need to take, though I have seen programs suggest taking courses in calc-based probability and real analysis. I took Calc I about 4 years ago and got a C. I took Calc II three years ago and got a B+. I've barely touched calc since. The options I've considered are: 1) Review Calculus principles for a couple weeks before the semester starts and begin Calc III. Try to get a good grade and drop if necessary. 2) Retake Calc 1 this spring and take Calc 3 in the fall (maybe summer). An advantage to this plan is that some programs request you have at least a B for your prereqs, which I could do for Calc 1. Any thoughts are appreciated. Thank you.
  12. Hi, I'm an ivy grad who majored in Economics & Statistics, 3.7 cumulative GPA, 167 Quant/165 Verbal on GRE. I've been doing strategy for a big tech company the past 2 years and been functioning as the go-to analytics/data science person on the team. Now I want to make a full-on transition to data science (goal is to become a ds at a startup!) and am realizing that I need more training in math and statistics to thoroughly understand the stuff I'm doing. Data Science Masters at Stanford, Harvard, and Columbia are my top choices. I'm also considering Statistics masters as well, since I want to hone in on the modeling/statistical part of data science. Although I have a ton of projects and experience at my current job & Kaggle applying machine learning/statistics, I don't have any research experience. I took 2-3 machine learning/data mining courses and 4-5 econometrics classes in college, and plan to get 2 rec letters from each field. I also did an online certificate program from MIT in Big Data. Do you think I stand a chance for statistics masters or data science? Would also appreciate any and all tips on crafting out my SOP. I'm so much more used to writing professional resumes... Thank you!
  13. Hi everyone, This May I graduated with a sociology degree. My goal is to become a social science researcher. Because the field of social science research is going toward a quantitative direction, I plan to apply to applied statistics masters program this fall. After masters, I plan to work in the Industry for a few years, and then apply for a social science PhD. (economics, public policy, political science, sociology..). I will really appreciate it if you can give me some advice. Undergraduate Institution: Top 10 Liberal Arts College Majors: Sociology Minor: Statistics GPA: 3.73/4.0 Math/Statistics GPA: 3.82/4.0 Type of Student: International Asian Male Related Courses taken: Calc II (4.0/4.0) Calc III (3.7/4.0) Linear Algebra (3.7/4.0) Probability (3.7/4.0) Econometrics (using Stata) (3.3/4.0) Applied Multivariate Statistics Analysis (using R) (4.0/4.0) GRE General Test: V:165/Q:167/W:5 Research Experience: None in statistics or Math. Two summers of research assistant experience for a sociology professor (not quantitative). One year of teaching assistant experience for social theory courses. A conference presentation at 2019 American Sociological Association Annual Meeting. Working Experience: Research Assistant for a large social science research organization since this July. Working on projects that heavily involve quantitative analysis (Stata, R, SPSS, SAS...). Collaborating with senior researchers on a quantitative research paper for journal resubmission. Letters of Recommendation: Two from math/statistics professors (probability and Applied Multivariate Statistics Analysis) who told me that they will write strong letters of recommendation. For the third one, I am considering asking either my sociology advisor (who knows me very well and views me very highly in terms of social science potential. But he does not do quantitative work), or a senior researcher that I am working with on a quantitative project at work. Currently considering Masters programs: Berkeley statistics CMU statistical practice UNC Data Science and Analytics Wisconsin statistics Michigan applied statistics NCSU statistics Cornell applied statistics UCLA applied statistics Ohio State applied statistics Rice professional statistics Georgetown applied math and Statistics Also considering these masters programs: Columbia Quantitative methods in Social Science Chicago Computational Social Science Do I have a shot in getting into these programs? Should I apply to more lower-ranked programs? What are other statistics programs that would be a good fit for my level of background? Should I ask my sociology advisor from college or a senior researcher at work to write me the third letter of recommendation? Thank you!
  14. Based on some searching on here, I tried laying down some estimates for what GRE minimum scores are needed for the various schools that offer a Stats MS program. I was wondering if people could critique this list? Thanks! 159 Q minimum target score for unranked/very low ranked schools 161 Q minimum target score for the lower ranked USNWR schools 164 Q should be sufficient for most ranked schools 165 Q is a minimum target score for almost all of the ranked schools
  15. Hi everyone!! Recently I have been admitted to the Stat MS program at Stanford & U Chicago and am struggling. I will try to advance to PhD after MS, but I don't know which school will offer me a better chance? I heard that Chicago has a good PhD prep and many research opportunities. I am not sure how Stanford is. But Stanford Stat ranks higher than U Chicago... Chicago Pros: - Tuition reduction (25%) - Good preparation for PhD - More research opportunity Cons: - Not as well-known as Stanford - Location is not as good. Stanford University Pros: - 1st in the country - So many well-known professors, a potential for recommendation letters and research opportunities Cons: - Not sure about placements - A lot of MS students, not sure if the professors will be willing to offer research opportunities. - Maybe the PhD prep is not as good as that in Chicago.
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