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  1. statfan

    Preparation for (Bio)Statistics PhD

    It may be due to weakness in other parts of their applications. It is very common that strong applicants have several phd-level statistics courses and I personally think it helpful to get exposed to grad courses early to see if graduate school fits you. Another advantage of doing this is that you can move onto research faster than others.
  2. statfan

    Preparation for (Bio)Statistics PhD

    Many students who went to top schools in the US in my school had taken multiple graduate level stat courses such as probability theory/statistical inference. I agree that real analysis/linear algebra are very important but other math courses are much less related to statistics. It may be a good idea to go to stat masters as a stepping-stone to phd and make up the real analysis background.
  3. statfan

    Preparation for (Bio)Statistics PhD

    I disagree with this. Doing well in grad level statistical inference and/or probability serves you two purposes. (1) It shows your aptitude for grad level research. (2) Grad classes tend to be much smaller and it is easier to establish close relationship with your prof. This can result in a great letter from a well-known faculty member cuz grad course instructors tend to be more senior. Taking grad level analysis courses would definitely help too and if you do well in them, you will be well ahead of most applicants. However, this does not necessarily requires a math master. Taking abstract algebra/geometry certainly wouldn't hurt but under time constraint, you would want to focus on the most important things.
  4. Your grades should be fine for the schools you applied but your math background is relatively light compared to strong applicants. You would want to have at least one mathematical statistics in your transcript, perferrably two. Maybe the problem lies in your letters. Generic letters talking about how well you did in their classes won't help for phd application, instead you would want to have letters talking about your research. Also, having one or two amazing letters from top faculties could dramatically improve your chance.
  5. The admission process is very complicated and no single factor plays a decisive role. GPA is only meaningful given certain context. A lower gpa may be more impressive at a prestigious instituition than a perfect gpa from an unknown institution. People from lower-ranked instituition will have a much tougher battle. Also, your math/stat gpa matters much more than the overall gpa. What is your math background? How well did you do in each course? For example, if your B's are in real analysis/linear algebra/math stat, that may be unfavourable. Your recommendation letters play an even more important role than the GPA. If you get strong letters from eminent faculty members highlighting your research potentials, that would really help you. I agree with bayessays that your verbal score is so low that it would raise concerns about your ability to communicate in English. Though verbal section of the GRE is one of the less important aspects of the whole application but still you do not want to stand out in a bad way. I would say at least aim to get 50th percentile in order not to be screened out.
  6. statfan

    Stats Masters Chances

    Your math/stat gpa matters much more than your cumulative gpa and unfortunantely your major gpa turns out to be much lower than your overall gpa. Although masters are much less competitive than phds, your consistent B's in math courses is still a huge concern. Without evidence of strong math skills in your other part of application, it would be unlikely to get into top masters programs. I would advise you to look into some programs ranked 20-30, or do well in math GRE to show that you actually have sufficient math skills.
  7. Only Stanford requires the math GRE. UW and Columbia recommend it. However, neither the general GRE nor the math GRE plays a decisive role when it comes to admission. Math/stat background and recommendation letters play a much more important role than the GREs.Time is a fixed constraint and you should prioritize the things that matter most. I wouldn't sweat too much on the GREs but instead focusing on research and upper-year/grad level math/stat courses.
  8. You are missing the point here. GRE is a filter and they only care about the quantitative section. You should score high in quant in order not to be weeded out during the screening process. You would be fine if you do not bomb the other two sections. Except a few schools, others do not care about the math GRE. That being said, do not submit the score unless you are very confident of doing well. Also, OP did not ask anything about the application fee, it's up to OP to consider this and I don't understand why you brought this up.
  9. What is your math background and how did you do in your math/stat courses? I am asking because this is much more relevant than your overall gpa. If you did uniformly well (mostly A's) in your math courses, then you may stand a chance of getting into good schools. Otherwise, admission committees may doubt your ability to do actual math given your low gre score and you may be weeded out in the screening process in some schools.
  10. Thank you very much, this is much more reassuring as I got mostly A+ and A's in my core math and stat courses. I have a few very low grades in finance/actuarial science though. I just done my real analyisis exam and I don't feel that I did very well. I am afraid that I may end up with high 70s or low 80s. In many Canadian universities, we do percentage grading, so that would correspond to B+ or A- (77-79 B+ 80-84 A- 85-89A 90-100 A+). Should I take Lebesgue Integration to remedy this? Would admission committees refer to the grading scheme on transcript to interprete the percentage grade as high 70s/low 80s does not sound impressive at all.
  11. When you go over the transcript, how would you assign weights to courses from different disciplines? (eg. from 1-10 scale with 10 being the most important) 1. Calculus/Linear Algebra 2. Real analysis/Measure theory 3. Other pure math courses (eg. geometry/abstract algebra) 4. Undergraduate statistics courses 5. Graduate statistics courses 6. Courses from other quantitative disciplines (eg. actuarial science/physics/chemistry/finance) 7. Electives 8. CS courses
  12. Few masters fund students. The masters that fund students are generally research-based and most students finally pursue a phd. I heard penn state and florida have a funded master.
  13. You have solid grades in a number of proof-based math courses so occasional slip up won't matter much. Many applicants do not have any research experience, so you definitely have an advantage over them. Along with recommendation letters from well-known professors, I think you can get into most schools you listed, if not all. Actually, you are way under applying, probably include some top schools in your list. I'd say you stand a good chance at top 10 stat phd.
  14. statfan

    PhD Profile Evaluation

    I don't think that you need TOEFL score if you did your undergrad in the States, even if you are not done. You have high grades in upper level math courses so your occasional lower grades won't matter much. Most departments don't care about your GRE verbal and writing unless you really bombed it. 154 verbal is a respectable score and you will be fine with that score. Your overall profile is very strong and I think your lists are fine. Most top phd programs admit a lot of international students, what they really care about is that if you have the potential to make contribution in this field. That being said, they would prefer a qualifed international student than a mediocre domestic student.
  15. 88% is a respectable score and I doubt that it will hurt your chances, actually it may help you if you come from a lesser-known school. It is not true that admission commitees expect higher gre math scores from international applicants. The fact that international students have higher scores than domestic students is simply because those who scored poorly did not submit the result.

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