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  1. statfan

    Biostats at McGill

    U of T biostat department is pretty much unknown and UBC has a very small department. Mcgill biostat is highly regarded in Canada and so is Waterloo.
  2. statfan

    2019 Statistics PhD Applicant

    You have a very strong profile coming from a well-known school, so you should apply to mostly top shcools. The UC programs you listed are far removed from top ones and are not competitive as you thought. Your original list seems good and maybe you should apply more aggressively by removing schools like Vanderbilt and JHU since they don't have a very strong department. I am sure you definitely can get into some top 10 programs, if not all.
  3. statfan

    2019 stats profile eval

    Your odds depend on the school you attended and the letters. There is a big difference between Toronto/Waterloo and say Western. Sometimes the decision really comes down to one single letter.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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
  15. 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.

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