permanent_gradstudent Posted September 17, 2020 Share Posted September 17, 2020 (edited) Type of Student: Domestic White Male Undergrad and Graduate Institution: Large State School (~Top 20 Public, Top 60 USNews General Ranking) Undergrad Major: NeuroscienceGPA: 3.45 (BSc) Grad Degree: Biostatistics (MS) GPA: 4.00 GRE General Test: 165 V/ 168 Q/ 5.5 AWA Programs Applying: Statistics/ Biostatistics PhD Research Experience: 2.5 years as data analyst/statistician in academic research lab. One first-author publication, two "co-first-author" publication (so second-author), another second-author, and a a handful of 3-4 poster presentations including one oral presentation with a "top undergraduate research" award at a local/institutional research symposium. All of this research very epidemiological/clinical (e.g. clinical prediction model of outcome, large cohort studies), no formal math or statistics work (outside of applied data analysis). In addition to statistician position, currently collaborating with a clinical lecturer to build out a Python course by aggregating python resources, simulating data and creating assessments for course projects Awards/Honors/Recognitions: Full tuition undergraduate scholarship; Two fellowships/honors programs in undergraduate (mildly competitive but completely unrelated to statistics); Small/partial tuition graduate scholarship; Summer 2020 scholarship to attend UW's SISMID; Letters of Recommendation: Collaborative clinical lecturer from Python work mentioned above (Clinician, so would it be better to identify a third writer with a quantitative PhD rather than clinical degree?) Professor with whom I've worked with in research outside of coursework Thesis supervisor and previous professor Math/Statistics Grades: Undergraduate: Multivariate Calculus (A), Data Science (A), Experimental Design (B), Applied Regression (C) Graduate: Applied Regression (A), Statistical & Probability Theory (A+), Health Data Science (A), Python for Data Analytics (A), Mathematical Methods for Statistics (A+), Machine Learning (A), Biostatistical Methods (A) and currently Linear Models, Statistical Learning, Neural Data Science Programming/ Software skills: R, SAS, Stata, Python, SQL, MatLab (basic) Note: I'm worried about my relatively poor and less-quantitative undergraduate performance (in general and in the few statistics courses I took). My recent academic performance has been much improved, and I'm hoping that some of the research experience/background might be able to moderately compensate. I'm also unsure if my graduate coursework is sufficiently rigorous wrt math/theory courses to be competitive for any statistics programs. Schools: Currently casting a wide net with applications to both Stat and Biostat programs, but mostly as I am unsure how to best evaluate how competitive my application is. I'm currently assuming that my school list may be optimistic and should include a few more realistic options, but would greatly appreciate any feedback! In no particular order: Carnegie Mellon - Stats Washington (Seattle) - Biostatistics Emory - Biostatistics Johns Hopkins - Biostatistics Yale - Biostatistics UNC - Biostatistics Brown - Biostatistics Vanderbilt - Biostatistics Virginia Commonwealth University - Biostatistics Virginia Tech - Statistics Duke - Biostatistics Edited September 17, 2020 by permanent_gradstudent Link to comment Share on other sites More sharing options...

bayessays Posted September 17, 2020 Share Posted September 17, 2020 Your math background is too thin to get into any ranked PhD program in biostatistics. All worthwhile programs require a linear algebra course, at a bare minimum, which you don't seem to have. You need to take more math. Link to comment Share on other sites More sharing options...

permanent_gradstudent Posted September 17, 2020 Author Share Posted September 17, 2020 1 hour ago, bayessays said: Your math background is too thin to get into any ranked PhD program in biostatistics. All worthwhile programs require a linear algebra course, at a bare minimum, which you don't seem to have. You need to take more math. Sorry if my course section isn't very descriptive, the "Mathematical Methods for Statistics" was a combined section of some calculus and the majority of linear algebra, and the Linear Models course in which I am currently enrolled is a PhD level course of applied linear algebra Link to comment Share on other sites More sharing options...

StatsG0d Posted September 18, 2020 Share Posted September 18, 2020 (edited) 16 hours ago, permanent_gradstudent said: Sorry if my course section isn't very descriptive, the "Mathematical Methods for Statistics" was a combined section of some calculus and the majority of linear algebra, and the Linear Models course in which I am currently enrolled is a PhD level course of applied linear algebra The Mathematical Methods for Statistics course is not a substitute for a standalone, proof-based linear algebra course taken within a math department, and since your linear models course only covers applied linear algebra, this would also not satisfy admissions criteria. It seems you have not taken any proof-based math courses. I think most departments would automatically reject you for this. Maybe some lower-ranked biostatistics departments who are only focused on applied work would accept you, but I still think, at best, you would be a marginal case. At a minimum, you should take a proof-based linear algebra course in a math department and Analysis I. If you add on Analysis II, you give yourself a tremendous boost and would be competitive for biostats programs outside Washington and stats programs outside the top-15. Add on something like complex analysis or abstract algebra, and you will have a good shot almost anywhere. You should note that admissions for stats/biostats are much more competitive than they were a half decade ago when I applied. With COVID-19, probably more people are going to be applying for grad schools making it even harder. Edited September 18, 2020 by StatsG0d grammar Link to comment Share on other sites More sharing options...

permanent_gradstudent Posted September 18, 2020 Author Share Posted September 18, 2020 I appreciate the detailed feedback from both of you! I know there are opportunities to take Analysis I and a more thorough Linear Algebra course, and possibly a later Abstract Algebra course. It certainly sounds like it would be to my advantage an applicant (and statistician) to enroll in some additional theory coursework and build these foundations for a more competitive Fall 2022 application Link to comment Share on other sites More sharing options...

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