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2021 Applicant Profiles and Admission Results for Statistics/Biostatistics


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I found the applicant profiles and admission results over previous years to be helpful while selecting the schools I chose to apply to, and now seems like a good time to start the thread for this year. Copy the template below and fill in as much info as you would like. Keep in mind that you can't edit your post for very long after posting, so it may be good to wait until you have most of your results before posting.
 
Here are some links to threads from previous years: 20132014201520162017201820192020.
 
Below is the template:
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.)
Math/Statistics Grades:  (calculus sequence,  mathematical statistics, probability,  real analysis 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
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Undergrad Institution: Ivy League
Major(s): Mathematics-Statistics
Minor(s):

GPA: 3.8999

Type of Student: Domestic Asian

GRE General Test:
Q:
169
V: 164
W: 5.5
GRE Subject Test in Mathematics:
M: NA

TOEFL Score: NA
Grad Institution: NA

Concentration:  NA
GPA: NA

Programs Applying: PhD: Statistics, Biostatistics, ML

Research Experience: Freshman research in social work examining social media data,  publication with  name far back, Sophomore Biostatistics REU: First author paper at PSB, 2 year of research in statistical Neuroscience at home Institutio, publication with name far back.
Awards/Honors/Recognitions:  Nothing really
Pertinent Activities or Jobs:  Tutor/TA

Letters of Recommendation: 1 from Assistant Professor in Linear Algebra Class I did well in, probably not well known in stats (just a did well in class rec probably, but I was pretty interested in his research and we talked a bit). 1 recommendation from Sophomore REU prof. Probably extremely good, but he's a prof at a pretty unknown school. 1 recommendation from statistical neuroscience prof. He's extremely well known but I didn't do too hot in his lab so probably rec was just "this kid is persistent and can grind".

Math/Statistics Grades:

Bunch of lower division classes (A).

Real Analysis I/II - A

Abstract Algebra I  - B+

Fourier Analysis - B

Measure Theoretic Probability - A-

Numerical Analysis - A+

Analysis of Algorithms - A

Artificial Intelligence - A

Statistical Machine Learning - A-

Bayesian Statistics - A

Statistical Inference -A

Causal Inference (CS) - P (covid)

Abstract Linear Algebra - P (covid)

Applying to Where: (Color use here is welcome)

Stats:
School - University of Michigan
School - University of Washington
School - Duke

School - CMU
School - University of Washington
School - Wisconin-Madison

School - University of Texas Austin (waitlisted- then accepted)
School - UCLA (ghosted probably rejected)
School - UNC (ghosted probably rejected)

School - Cornell (ghosted probably rejected)

School - Rice

Biostats:
School - University of Washington
School - Harvard

Misc:

School - MIT (SES)

School - Georgia Tech ISYE (ML Program)

School - Northwestern IEMS

Advice for Posterity and Reflection:

Overall I'm pretty happy with my results and I'm pretty excited to be attending Duke. One caveat is that I severely underestimated my application (thought I would get into maybe one of UWashington, Duke, Mich). I didn't think I had a chance at Harvard/Berkeley  because of my so-so performancein upper division math classes and lack of graduate coursework , I didn't apply. My rec writers put a cap on schools beforehand (totally reasnoble given my paranoia) so I overspent my school allowance on safety schools. So future applicants please take risks because the regret is real. Tbh I probably wouldn't have gotten in to Harvard/Berkely but now I'll never know.

Some general advice

- all 3 of your letters don't have to be crazy strong. I think I only had 1 really strong letter that sang about my potential as a top researcher. While he was from a pretty unknown school he had sent quite a lot of students to top programs so that might have helped. The other letter from the neuroscience prof I did research for probably wasnt that great as I wasn't stellar and probably one of his worse students (but he has pretty good students). this letter probably said I was competent, hardworking and easy to work with. My last letter likely just spoke to my interest in math and that I was mathematically competent. So not crazy strong letters.

- undergrad school prestige matters a lot. So if you're from a top grade deflated school and have bad grades still shoot for the top! Hopefully my ehh profile encourages ya'll.

- Harvard/UWashington Biostatistics are not safety schools (typing this sentence, it seems obvious). I thought Biostatistics programs are much less competetive than statistics. But obviously that's not really the case as I got rejected by UWashington biostat and into UWashington Stat. Also I went to Harvard Interview day and people were super accomplished even before getting cut. I'd put those tier of biostat programs on the same competitiveness as UMich-Duke-UWashington Stats (probably difference that they place more emphasis on undergrad research and a little less on math).

- That being said if you're interested in Stat seriously consider top Biostat programs they do super cool work and I feel like I would have been very happy at Harvard if I didn't certain offers I did.

- Don't take math classes you're not interested in just to have more math classes. That's how my B in fourier analysis happened.

- Operations research programs are much less competetive (outside like MIT/Berkely) if you're interested in applied stats stuff.

- Hot take: I disagree with the prevailing wisdom that the SOP doesn't matter. I think Recs + Grades are much more important but with so many people applying I think that demonstrating that you can coherently express your research experience and that you know what type of work academic statisticians do via your research interests can move your application from the "consideration pile" to the "accept" pile.

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Undergrad Institution: Low-ranked, medium-sized public university known for engineering
Majors: Mathematics, philosophy
Minor: Applied statistics
GPA: 4.00
Type of Student: Domestic white male

GRE General Test:
Q
: 169 (94%)
V: 166 (97%)
W: 6.0 (99%)
GRE Subject Test in Mathematics:
M: N/A
 
Programs Applying: Statistics and mathematics PhDs

Research Experience: I attended an REU in coding theory. From this project, I got an authorship on a paper. I also attended a well known SIBS program and have done some statistics consulting for my campus writing center.
Awards/Honors/Recognitions: I received a few department awards for "excellence in mathematics" and that sort of thing, and I've been a part of a few winning teams in regional math competitions. I also won a few awards for writing projects and have a pretty solid record of activities outside of math and stats.
Pertinent Activities or Jobs: I have minimal experience as a TA for calculus ii, but I have a few years of experience tutoring everything from math and stats to history and writing.
Letters of Recommendation: All of my recommendations came from professors in my department, none of whom are famous per se but each of whom knows me well.
Math/Statistics Grades:

  • Abstract Linear Algebra (A+)
  • Group and Ring Theory (A+)
  • Commutative Algebra (A)
  • Algebraic Geometry (In progress)
  • Advanced Calculus I (A+)
  • Advanced Calculus II (In progress)
  • Measure Theory (A+)
  • Mathematical Statistics (A+)
  • Introduction to Probability (A)
  • Financial Mathematics (A)
  • Design and Analysis of Experiments (A+)
  • Regression Analysis (A+)
  • Introduction to Applied Statistics I / II (A+ / A+)
  • Introduction to Topology (A)
  • Algebraic Topology (In progress)
  • Dynamical Systems (A)
  • Partial Differential Equations (A)

Any Miscellaneous Points that Might Help: I have a pretty long list of various activities that each on their own aren't special but, when united together, form a CV so mean it makes medicine sick. (I just have a lot of extracurricular stuff. It's like I went to high school for college.)

Applying to Where: (Color use here is welcome)

  • Boston University (Math) / Rejected
  • Michigan State University (Math) / Accepted (Declined)
  • Northwestern University (Math) / Rejected
  • Pennsylvania State University (Math) / Accepted (Declined)
  • University of Illinois - Chicago (Math) / Waitlisted (Declined)
  • University of Maryland - College Park (Math) / Pending
  • University of Michigan - Ann Arbor (Math) / Pending
  • University of Wisconsin - Madison (Math) / Rejected
  • Carnegie Mellon University (Stat) / Accepted
  • Columbia University (Stat) / Rejected
  • Duke University (Stat) / Accepted
  • North Carolina State University (Stat) / Accepted (Declined)
  • Ohio State University (Stat) / Accepted (Declined)
  • University of Chicago (Stat) / Accepted
  • University of Michigan - Ann Arbor (Stat) / Pending
  • University of Minnesota - Twin Cities (Stat) / Pending
  • University of North Carolina - Chapel Hill (Stat) / Accepted (Declined)
  • University of Wisconsin - Madison (Stat) / Accepted

Reflection: I was quite anxious about my applications because I felt that my background was not brimming with research and gleaming with prestige, and I made two mistakes as soon as I finalized my list of options. Firstly, I should have been more assertive with my picks of stats programs. I didn't need to apply to every good school that I thought might accept me, and I could have reached just a little higher just for the sake it. Don't get me wrong - I'm extremely pleased with my outcomes and grateful, too. I did not expect to get accepted to Duke or CMU or UChicago and am still limited in my imagination to dream at this level. I probably could have passed on NCSU and UMinnesota, which are not as good fits for me, and instead thrown my hat in at Harvard or Stanford literally for no other reason than to see if it might've been possible. I probably wouldn't have chosen them if I did get accepted I suppose, but I admit that I do wonder. Either way, though, I realize that it would have been totally okay to take a gap year if I didn't get any acceptances for the reason that I shot too high and didn't play safely, and it would have saved me a few hundred dollars too. 

Secondly, I should not have gotten too excited about math programs - there's nothing wrong with math, but it's obvious to me now that I am supposed to devote my life to studying statistics. I hadn't spent a whole lot of time doing statistics, and the bells and whistles of Pure Math were always tempting me; any time I browsed YouTube or went to a math competition or attended Math Club, that spark of intellectual curiosity inside of me would jump a bit higher. I kept convincing myself that I only was considering statistics as a back-up because it's more profitable or less competitive. Somehow stats were an abhorrence, a perversion, a delinquency, and only were disguised as "a real job" in order to woo weary sailors away from that Ithaca in the ethereal Arts & Science College up above. It took some discussions with my professors and with my peers to climb down from that notion. Now I am more aware of what I want to do with my PhD, writing my statement of purpose became easier for statistics programs than for math ones.

I still feel very strangely about my results, honestly. From my perspective, this is the first time in my life that I've felt thoroughly verified for something that I've cared about. I'm not especially clever nor do I have outstanding achievements. I don't attend a prestigious university. I'm like a gritty country boy with a bit of a personality and some facility with math. What helped me stand out, then? If I were to guess why my applications to statistics programs were so successful, I would say that I presented a clear and honest sense of what my goals are and why I'm applying to grad school in my statements. I think of myself as a writer rather than a statistician, and I want to train myself to be the best darn science writer I can be. I think statistics is a deeply philosophical endeavor full of challenges for writers, but it also notoriously invites opaque reasoning when efficiency is prioritized over rigor. This problem, I feel, invites people like me whose competencies conspire to address it through good expository writing, and that is the main reason why I find the subject attractive. Meanwhile, I have some technical skills and want to continue learning and studying interesting problems. I didn't pretend that I am taken by unclarifiable passions for machine learning or statistical genetics, which I don't accuse *you* of doing, but I found it hard to interrogate myself to the point that I could actually say more than that I have similar passions. The specificity and authenticity of my motivation was probably the most affecting part of my application.

Toward this aspect of the journey, then, I would advise readers like me who come from more-or-less humble backgrounds to think seriously about what it is that you contribute. Prestige schools are like carnival games; it's worth the price to play. Just remember that in the academic elite people need to know who you are. You don't want to be Charlie Bucket who stumbled upon the last Golden Ticket and found his shoes on the ceiling by accident. I'm facing the fact that I will never feel like the smartest person in the room again, and I'm okay with that (although it's kind of spooky to think that there's going to be someone with a high IQ hiding under my bed). I'm excited to contribute my own experiences and ideas to whichever department I choose, and I have to know that I have that or else I won't be able to function when I get there.

Not to legislate on the exception to a rule, but considering my exceptional (meaning atypical, not superior) case, I would like to conclude that there is no "correct" way for one to improve one's applicant profile. As they say, there are many paths up the mountain, but the view from the top is the same. I may not know the first thing about mountaineering, but I think it's a bit like climbing the academic ladder. There are a certain number of cliffs or steep inclines that you will find yourself facing when you choose the Road Less Traveled. You can probably find the right equipment, but you need to be a little lucky to find a good deal or else it's going to be extremely resource expensive. Actually, I don't know how to bring this analogy together.

I hope my reflections have been entertaining if not insightful as well as inspiring without being pretentious.

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Undergrad Institution: Large private school (top 100 US News)
Major(s): Statistics 
Minor(s):
 Mathematics
GPA: 4.0
Type of Student: Domestic white male

GRE General Test:
Q:
 162 (78%)
V: 158 (79%)
W: 5.5 (98%)
 
Programs Applying: Statistics PhD
 
Research Experience: About 10 months at my current school (undergrad). Bayesian research in environmental statistics, submitting manuscript within the next month or so.
Awards/Honors/Recognitions: Just the usual dean's list, full-tuition academic scholarship, etc.
Pertinent Activities or Jobs: Paid research assistant, no TA experience
Letters of Recommendation: 1 very strong from research advisor (assistant prof). He told me he would love to have me as a graduate student. 1 probably very strong from an associate professor I took two stat classes with. She told me I was her "ideal student". 1 fairly strong from an associate professor I had for Bayesian stats. We talked a decent amount in office hours, and he was probably impressed that I had already learned all the material on my own.
Math/Statistics Grades:  Calc 1-3 (A), Theory of Analysis 1 (in progress), Fundamentals of Mathematics (proofs, A), Probability and Inference 1 & 2 (A), ANOVA (A), Intro & Applied R programming (A), Intro to SAS programming (A), Intro to Unix/Shell programming (A), Nonparametric Stats (A), Data Science Methods (A), Regression (A), Computational Linear Algebra (A), Elementary Linear Algebra (A), Bayesian Stats (A), Analysis of Correlated Data (in progress)

Applying to Where: (All Statistics PhD)

Colorado State University - Admitted on 1/12. Offered GTA with funding of $18,450/9months, health insurance included.
Baylor University - Admitted on 1/28. Offered GTA with funding of $20,700/9months with additional $7k fellowship for the first year, 80% health insurance subsidy.
University of Missouri - Columbia (Mizzou) - Admitted on 2/15. Offered GTA with funding of $18,026/9months, health insurance included.
The Ohio State University - Admitted on 3/2. Offered GTA of $21,280/9months, 85% health insurance subsidy.
 
University of Illinois at Urbana-Champaign (UIUC) - Rejected on 2/24.
 
Rice - pending as of 3/11.
Texas A&M - pending as of 3/11.
University of South Carolina - pending as of 3/11.
 
Reflection and Advice: 
I never took any graduate level courses and I'm graduating in just 3 years. I know that if I stayed for another year and took more math classes that I would have probably been competitive for higher ranked programs, but I'm very happy with the acceptances I have gotten, and ranking isn't that important to me since I am almost positive I want to end up in industry anyway. What started out as one of my last choices (primarily due to ranking) actually ended up being my top choice (and the offer I decided to accept). I also think that not having finished real analysis yet may have had a negative impact on my application, but it ended up being okay. My GRE Q score is also quite low, and I did submit it everywhere, even where it was stated as "optional, but recommended" due to covid.
 
For future applicants, I would suggest talking to your professors about graduate school and which programs would be good for you (and where you would be competitive). My LoR writers all gave me great advice and expressed confidence in my success even though I was very unsure of whether I would get accepted anywhere or not.
 
In retrospect, I probably would have applied to some Biostat programs just to have a wider range of options, but I also am completely happy with my acceptances. I'm just really passionate about learning and doing research, so I am excited about the opportunity to start grad school this year.
 
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  • 5 weeks later...
Undergrad Institution: UC Berkeley + Community College (1 yr)
Major(s): Statistics || GPA: 3.8 (overall at Berkeley) — lower for math/stats (see below)
Type of Student: Domestic Asian Male
 
GRE General Test:  Q: 166 (87%)  | V: 164 (94%) | W: 4.5 (80%)
Letters of Recommendation: 2 teaching/adjunct faculty in math/stats + 1 Electrical Engineering Prof.
 
Math Grades:  
    Calculus I-II: A 
    Multivariate Calc. +  Diff Eq. + Lower Div. Linear Algebra (Community College): A
    Linear Algebra (after graduating ) B+
    Real Analysis (via UIUC’s NetMath) : A
 
Other Grades: 
    Probability: A  || Math Stats: A+
    Statistical Computing: A+ || Linear Modeling: B+
    Time Series Analysis: B+  || Statistical Learning: A+
    Intro to CS: A 
 
Research Experience: A published public policy paper + Applied factor analysis research at an air pollution lab.  
Work Experience: 3 years of work experience in clean energy/healthcare.
Miscellaneous: Received NSF Honorable Mention. 
 
Schools Applied:  Only applied to Stats PhD Programs in CA.  
Given my interests, I would have applied to other schools with environmental/spatial/applied bayesian stats research. 
 
1. UC Santa Cruz - Statistics / Admitted  on Jan 28th / Accepted
    Funding: 26k/9months + 3k summer fellowship + healthcare. Health insurance included.  2Q TA & 1Q Fellowship.
2. UC Santa Barbara - Statistics & Applied Probability / Admitted on Jan 27th / Declined
    Funding: 22k/9months + healthcare.  TA ships. 
3. UC Davis - Statistics / Waitlisted, Admitted to MS with partial funding. 
4. UC Riverside / Waitlisted 
5. UC Irvine / Pending
6. UCLA Biostats / Rejected on Jan 27th
 

 
Reflections:  I came into undergrad wanting to study environmental policy.  I discovered stats my sophomore year and had to go back to community college in order to switch!  Even after switching to stats, I had ZERO intentions of going to grad school.  I had a very un-linear path to get here. 
Given the rise in the competitiveness of admissions, I feel very fortunate to have acceptances into two programs in beautiful (and expensive) places.  😄 
 
Advice:
My guidance may be more useful for “atypical” candidates or candidates whose undergrad math background is not particularly deep. 
 
1. Depth of math background matters a lot …  
Admissions are becoming even more competitive. So the depth of math background is apparently becoming more important to differentiate oneself from other applicants. 
The bare minimum is Real Analysis & upper div. algebra but I’d take more if time/budget allows. 
If you don’t have a strong math background, it’s ok.  See pt 2.
 
2. … but there are ways to make it up, even after graduating.
If you want to improve your math background, I recommend NethMath, the UIUC program run by their math department that is fully online. 
It is well designed for remote instruction and is cheaper than enrolling as a non-matriculated student. 
It allows you to take classes while working as well.  
Another plus is that the transcript they produce is indistinguishable from UIUC's normal classes. 
 
I had some savings so I was tutored by a Math PhD to get some guidance in proof-writing for a few months.  
This was SO extremely helpful for improving my mathematical maturity, though adcoms won’t care about it. 
If you’re interested in that, contact someone like Alexander Coward: https://edeeu.education/director/alexandercoward
 
3. If you need to study & make up coursework, then do it full-time
Of course, not everyone has the means for this. 
That said, if you know you lack the math/coursework background to be a competitive applicant, then seriously consider studying full-time. 
Studying math while working a job is very difficult and inefficient.  There’s a momentum that comes with a full-time dedication. 
 
I mostly studied part-time and half-assed my job (during this period). In hindsight,  I would have just focus on studying for a few months & then find a job. 
Of course, the financial hit is significant but consider it good practice for living on a grad student budget. 😄
 
4. Domestic students: apply to NSF.
You’ll be forced to read journals and think seriously about your research interests.  It will also make you start your application materials early. 
I even got to get a professor at a perspective school to write a letter of rec for me. Through this, I got to talk to them get to know them.
 
5. Seriously consider taking a year or two off after undergrad.
A few reasons for this:
    I. The years in the “real world” have been so, so valuable to me.  Chances are, you’ll mature a lot. 
    II. I think some grad students struggle with choosing an advisor because they’ve never had a real boss. 
            Working under a boss or two will give you a better idea of what "a good advisor" actually means for you. 
    III. Learn how to adult. Make sure you live frugally. 
    IV. You’ll have savings!
Edited by bob loblaw
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Undergrad Institution: Big State School

Major(s): Math and Econ

GPA: 3.9

Type of Student: Domestic, white man

 

GRE General Test:

Q: 168 

V: 160

W: 4.5

GRE Subject Test in Mathematics:

It was canceled for the pandemic, might’ve taken it but who knows

 

Programs Applying: Statistics PhD

 

Research Experience: 

Year-long research grant in econometrics, leading to a paper (not published) but presented at a conference at my uni

Year-research assistantship, in the field of deep learning and NLP, paper to be published

 

Awards/Honors/Recognitions: Nothing special, university-specific awards

Letters of Recommendation: One letter from first research experience and another from the second research experience, last letter from a math professor that I had for many of my upper level math classes.

 

Math classes: Calc III (A),  Basic Concepts of Math (A), Real Analysis I and II (A), Linear Algebra (A), Differential Eqs (A)

Stat classes: Probability theory I (A), Probability Theory II (A), Mathematical Statistics (A), Data Analysis and Stats Computing (A), Intro to Machine Learning (A)

Misc classes: Mathematical Economics w/ Linear Algebra (A), Econometrics I and II (A), Python Programming (A), Data Science (A), Cloud Computing (A)

 

Applying to Where (All Statistics PhD):

 

University of Illinois at Urbana-Champaign Admitted

University of Michigan-Ann Arbor Admitted

University of Wisconsin-Madison Admitted

 

Carnegie Mellon University   Rejected

Harvard University   Rejected

University of Chicago  Rejected

Columbia University  Rejected

University of Washington  Rejected

University of Toronto  Rejected

UCLA Rejected

 

Rice University ~Ghosted~

UNC Chapel Hill  ~Ghosted~

UPenn ~Ghosted~

 

Reflection/Advice:

 

Very happy for the outcome but boy was it stressful. I probably could’ve skipped out on a few schools that weren’t as solid a fit but I was nervous re: covid so I just applied to a bunch. If you’re like me and prone to stress, my advice is to just not apply to grad schools during a pandemic! In all seriousness, I would recommend finding out how competitive your app might be from a trusted source (or this blog) as that is essential for your strategy of where to apply. Also, make sure you have enough time to apply, its extremely time-consuming.

Edited by JS99
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Undergrad Institution: Berkeley
Major(s): Data Science
Minor(s): Computer Science
GPA: 3.9 at time of application, 3.87 including fall semester
Type of Student: domestic asian women
 
I didn't really submit my GRE scores except where they were required, but here they are anyway:
GRE General Test:
Q:
 166
V: 164
W: 4.5
GRE Subject Test in Mathematics: didn't take
 
Programs Applying: Statistics PhD, a couple of computational applied math in there
 
Research Experience: No publications, but I had a couple of applied research projects I did in undergrad. I was also in the process of doing an applied project of my own this year.
Awards/Honors/Recognitions: uhh I don't think so
Pertinent Activities or Jobs: Tutored/TA'd probability and statistics. I also interned as a SWE at one of the big tech companies for 2 summers back when I thought I was gonna be a SWE. probably not too relevant but idk
Letters of Recommendation: One was a prof I took several classes with and taught for. One was a prof I had in fall semester that I really liked and we got along. The other was a professor in business school I had done a research project with. I think the first two are pretty well known professors in stats, but one of them is known more for teaching than research nowadays.
Math/Statistics Grades:  
calculus sequence: A's
mathematical statistics: A
probability: A
real analysis: B+ :(
linear algebra (upper and lower div): A, A+
I also had a bunch of other CS classes, both coding and theory and ML, which I had A's/A-'s in 
Any Miscellaneous Points that Might Help: took a grad class in CS theory, not really sure if this helped at all but I think it did help with showing my proof-writing ability since I got B+ in analysis

Applying to Where: 

Berkeley - Statistics PhD / Rejected 2/5
Harvard - Statistics PhD / Rejected 2/23
Chicago - CAM PhD / Rejected 3/17

Caltech - CMS PhD / Rejected 3/26
CMU - Statistics PhD / Rejected 3/4
Washington - Statistics PhD / Rejected 3/9

NYU - Data Science PhD / Rejected 3/17
Michigan - Statistics PhD / Accepted 2/8
NC State - Statistics PhD / Accepted 2/11

Minnesota - Statistics PhD / Accepted 2/4
UC Davis - Statistics PhD / ghosted (it's 4/15 now so this is a rejection)
UCLA - Statistics PhD / I can't tell if I've been ghosted or if I'm still on the waitlist but basically I didn't get in

UT Austin - Statistics PhD / Accepted 2/11

*Edit to add: all admits came with financial offers, Michigan was like 2700/month and the other three offered roughly 21k/9 months. all for TA
 

I was really happy with these results! I didn't break into the really top tier of schools, but I mostly got into big public schools. Oddly enough when I was applying I really wanted to go to Michigan but in the end I'm committing to UT Austin, which I thought was my safety due to its current ranking (but it turns out isn't that much of a safety?) and I ended up really liking. I am a little disappointed that I didn't get into a single California school since I'm a native Californian (they didn't even have the decency to reject me - they just ghosted me?? how rude) but I guess it's time for something new for me :) 

Edited by confusedbear
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Undergrad Institution: Asia QS rank around 150
Major: Humanities 
GPA: 3.61
 
Grad Institution in the same school
MA in Economics 
GPA: 3.9
Type of Student: International Male

GRE General Test:
Q:
 169 
V: 155
W: 3.5 
GRE Subject Test in Mathematics:
X

TOEFL Score: (R28/28/S21/W22) but most programs waived the condition.

Grad Institution: MS Statistics in US (Ranked 16~25)
Concentration: 
GPA: 3.78
 
Programs Applying: (Statistics PhD only)
 
Research Experience: Research experience in labor economics. I worked for a year, did a presentation but did not published the paper. Also I did a small project in a graduate statistics course.
Pertinent Activities or Jobs: (TA job in the previous program in Asia)
Letters of Recommendation:   One from Economics professor I worked with for my research and I did TA for him for two years. Two from Statistics Professors, and the last one was from the professor who taught me Honor Analysis 1.
Math/Statistics Grades:
 1) I did not took calculus sequence officially, but I learned them through courses like Mathematics in Economics and self-study . 
 2) Advanced mathematics for Engineers(Linear Algebra),  A, previous program in Asia. 
 3)Real Analysis(measure theory), B- , previous program in Asia.    4)Functional Analysis A, previous program in Asia.
 
(Do you see something strange?, I took measure theory and a functional analysis without a solid background in undergrad level analysis, and now
I am pretty sure I have to study again those subjects since I feel my background in analysis is much more solid then before) .
5) Advanced Calculus 1, A, US, almost the first course I seriously started to study real analysis. 
6) Honor Analysis 1, B-> A-(I retook it, in the back then I didn't want to quit so did not choose the option "W", US.
7) Currently, I am taking Honor Analysis 2, US.
😎Casella Burger Theory of probability and Statistics sequence(A,A), US.
 
Also, I took bunch of courses here and there such as Statistics in Economics(graduate) A, Asia, Econometrics(graduate), A, Asia, Micro-Econometrics(graduate),A, Asia, Regression course(graduate) A-,US, Design of experiments(graduate), A-, US.
 
Undergrad courses or master level courses in US: Intro to Machine learning(P), Time Series(A-), Multivariate Analysis(A), Statistical Computing(A), Regression Course(A),
, Undergrad Probability theory(A), and maybe some more in the previous program. 

Applying to Where:  PhD Statistics programs only
I applied to 17 Statistics programs ranked 20~55 in USnews.  Rest of the programs beside the three below, I got rejected.
School - University of Iowa / Admitted/ 2.28 / Accepted   
 (But they put me on the waitlist for funding maybe because I was not very enthusiastic responding to their program.)        
School - Colorado State University  / Admitted/ 4.13 / Accepted 
School - Rutgers University / Admitted/ 4.12 / Accepted
 
I am still hesitating about posting which could be easily recognized by people but I am indebted to people in here, so I am posting mine out of the responsibility and in a hope to improve information asymmetry between applicants and schools. I wish my profile and the results can give hope to future applicants especially those who plan to change their fields.
 
Firstly, I want to stress that if you start late with a weak mathematical background, you should never be hasty. Otherwise, you might end up spending much more time to study those prerequisite courses. Take a step by step, there is a reason why curriculums were constructed as the way they are.
 
For applicants who do not have a super strong profile, I suggest try to secure more than three letters. One reason is that, in my opinion, you should not be so sure about which professor would write a best letter for you especially when you are not the #1 in your department. I saw many people saying they've secured the best letters, but seeing their application results, I doubt it. On the other hand, even if you submit different combination of letters, they will probably have about the same power because a strong letter comes from a strong reason why they should recommend you. Still, I would suggest to secure more than three letters because you do not know which schools have a connection with your recommenders and this may important than you think. 
 
For the international students, when you plan to go master program in U.S. hoping for an opportunity, think twice. If you get admitted into top master program, I guess the risk becomes smaller but if you are not, then the risk becomes exponentially larger. If you were not competitive in your own country, think twice which factors would make you a different person after a year or two in U.S. Also, be aware that you may not have many opportunities for RA or TA even comparing to undergrad students because they have different sources which are only available to undergrad students and the resources for grad students go to PhD Students. So, ambitious international students who have already proved your competitiveness in your country but lacking strong letters are encouraged to apply for master program in U.S. If it is not the case, you should know about the risk before starting your journey, I have no intention to discourage anyone. This is more like I would have wanted to hear before I start this process. Actually similar stories apply to domestic applicants as well. 
 
Lastly, apply to as many schools as you are allowed to. The margin cost of applying to extra one program gets smaller by each iteration. So do not think about the cost of applications, think about the real cost that you have payed including your youth. 
 
I will not list names, but I really appreciate people who shared their knowledge and experiences in this forum.  
 
 
Edited by Stat01243
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Undergrad Institution: QS Asian U top 100
Major(s): Statistics
GPA: 3.78 after conversion
Type of Student: International male

GRE General Test:
Q:
 169 (94)
V: 152 (53)
W: 4 (55)

TOEFL Score: 100=25+25+24+26

Grad Institution: Same with undergrad
Major: Statistics
GPA: not good
 
Programs Applying: Statistics/Biostatistics Ph.D. programs
 
Research Experience: one methodology publication in CSAM, two application publications in domestic journals (text analysis and GLM), one theory paper under review
Awards/Honors/Recognitions: honorable mention for a poster presentation
Pertinent Activities or Jobs: TA at grad school, part-time lecturer at a corporation
Letters of Recommendation: two from profs with whom I worked on papers, one from advisor (strongest in terms of the personal relationships)
Math/Statistics Grades:  Calculus I & II, Linear Algebra, Mathematical Statistics I & II, real analyses, 20 statistics major courses in total (took about 95% of available major courses until graduation), database, digital logic
 

OSU - Statistics / Admitted in late Mar / Accepted
MSU - Statistics / Admitted in early Mar / Declined
U Iowa - Statistics / Admitted in early Mar / Declined
U of SC - Statistics / Admitted in mid Feb / Declined
UCSB - Statistics / Waitlisted - Admitted on Apr 14 / Declined
 
CSU, UCR - Withdrawn
 
... AND 15 REJECTIONS
 
I'm pretty happy in that I got into one of my very best options even though I did not earn MS in prestigious US programs and get recommendations from well-known American professors. I can say that the profile evaluations and program recommendations people make in this forum are quite accurate and helpful even for minority in the applicant population like me. @bayessays@Stat Assistant Professor@StatsG0d I truly appreciate your help and advices!!
Edited by statenth
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Undergrad Institution: Small, private liberal arts school
Major(s): Mathematics
Minor(s): Art History

GPA: 3.4
Type of Student: Domestic Female, white

GRE General Test:
Q:
 162 (78%)
V: 161 (88%)
W: 4.0 (55%)
GRE Subject Test in Mathematics: n/a
M: n/a

TOEFL Score: n/a

Grad Institution: No other grad experience.
 
Programs Applying: Statistics MA/MS only
 
Research Experience: None
Awards/Honors/Recognitions: None
Pertinent Activities or Jobs: Tutor/TA for Math department
Letters of Recommendation: 2 math professors, 1 math professor who was my advisor, & boss from TA job. I knew all of them well.
Math/Statistics Grades:  
Calculus II: A- 
Programing (Python): B+
Calculus III: B-
Differential Equations: A
Linear Algebra: B
Topology: C-
Probability and Statistics: B
Number Theory: A
Abstract Algebra: B+
Discrete Mathematics: A
Any Miscellaneous Points that Might Help: Nothing that I can think of atm.

Applying to Where:
UCI (MS) / Admitted / Declined
UCD (MS) / Rejected
UCLA (MS) / Ghosted (definitely rejected) Pending on 4/19
Columbia (MA) / Admitted with $10k scholarship & TA Grading job / Accepted
UVA (MS) / Admitted / Declined
UW (MS) / Rejected
 
Reflection and advice:
I decided to apply to graduate school pretty late in my senior year. Due to the pandemic, I worried that I would struggle to find jobs, so around September I decided to give applying a shot. Originally, I'd planned to apply to many more schools than I did. I thought I would almost certainly get rejected everywhere I was inclined to attend and had basically decided to take a gap year and apply again the next, so why waste money on sure bet applications? I thought I'd applied to schools that were mostly out of my reach, but I guess that wasn't the case. I was floored to get accepted to the programs I was. Though I'd done some research on the programs,  my reasoning for choosing the schools I did was mostly based on the undergraduate and PhD programs at the institutions. It turned out that finding information about Masters programs is a pretty tough task. I think I probably got accepted to the best programs I was going to, but I wish I'd done a little bit more research before accepting Columbia's offer. I was under the impression that Columbia was an excellent program (because the PhD program there is superb). However, it seems that Columbia's MA program accepts a higher percentage of applicants than do other Ivy League schools' Stats Masters programs. I'm happy with my decision, though.
 
I would recommend looking into the LinkedIn profiles of former students at various programs of interest to you to see how employable they are. If I could do it again, I would also reach out to alums to ask about their experiences, to help determine fit. The great majority of Columbia admits that I've had contact with had a math background, which surprised me, especially since the program isn't as theoretical as others I applied to. I wouldn't be shocked if this was the case with other programs, as well.
 
With time (after I applied), I realized that departmental websites have a huge amount of helpful information that is difficult to access. Taking a good amount of time to truly scour programs' websites would likely help in determining what you are looking for in a Master's education.
 
Disclaimer: It's totally possible that I was comparatively uninformed, going into the application process, since I had 2-3 months to do research between deciding to apply and applying.
 
I think I was probably on the lower end in terms of gpa/gre scores of accepted students to those programs that I got into. I think that my letters of rec were probably pretty humanizing, since I knew all of my recommenders very well. I imagine they talked about me, as a person, not as a student. This is because I go to a small school and was able to develop connections with them, which was likely evident in their letters. I also spent a long time on my personal statement and statement of purpose essays. For the most part, I ignored my grades and lack of experience in the field, instead opting to write a story about the most interesting aspects of my application. I don't know how much my letters of recommendation helped me, but I worked to make sure they weren't dry and showed off the best parts of who I am. I'm sure different admissions committees look for different strengths in their applicants, so doing research on what different programs like to see is always helpful. 
 
Honestly, I think that grad apps can't really go wrong, since there's always next year (which might be naive of me). I think putting a ton of pressure on yourself will only make your sops and personal statements worse. Especially since work experience and/or internships are such a help in getting into Stats programs, taking a gap year can only really help your application, as long as you use the time wisely. I hope this helps someone, and good luck to all the future Stats grad students out there!
 
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Undergrad Institution: Large T75 public school
Major(s): Statistics, Mathematics
Minor(s): Computer Science
GPA: 3.96
Major GPA: 4.0
Type of Student: Domestic minority male

GRE General Test: (not sent to most schools because of COVID)
Q: 167 (89%)
V: 165 (96%)
W: 5.0 (92%)

GRE Subject Test in Mathematics: NA
 
Programs Applying: Statistics, Biostatistics
 
Research Experience: 

  • REU at local university. Resulted in a solid bioinformatics publication in a decent journal. I was second author.
  • Summer Program in Biostatistics at Harvard. Not as research focused as I would have liked, but still a great experience.
  • Very applied and coding-intensive COVID project. The resulting dashboard and analysis were linked on my cv.

Awards/Honors/Recognitions:

  • Top student in honors intro to analysis (cash prize)
  • Top student in honors real analysis (cash prize)
  • Other small math and diversity scholarships


Pertinent Activities or Jobs: 
Nothing outside of activities related to aforementioned research

Letters of Recommendation:

  • REU professor
  • Math professor who was my informal advisor throughout my undergrad.
  • COVID project professor who I also had for multiple grad classes

None famous, but all knew me VERY well and promised to write excellent letters.

Relevant Coursework: 
three undergrad real analysis classes, grad measure theory, undergrad probability, grad measure-theoretic probability, two proof-based linear algebra courses, grad Casella & Berger inference, CS courses for my minor, and many other core math and stats classes.

Applying to Where: PhD only

Harvard - Biostatistics / Accepted

Stanford - Statistics / Rejected
UC Berkeley - Statistics / Accepted
Chicago - Statistics / Accepted
Harvard - Statistics / Accepted
CMU - Statistics / Rejected
UW - Statistics / Accepted
U Penn - Statistics / Accepted
Duke - Statistics / Accepted
Michigan - Statistics / Accepted
UNC - Statistics / Accepted
NCSU - Statistics / Accepted
Cornell - Statistics / Accepted
TAMU - Statistics / Accepted


Reflection:
I definitely underestimated my application. I kept telling myself that I would be happy if even one of my applications was successful. However, I received some excellent advice from my math professor: "apply to every school that you actually want to attend." As a result, I sent out 20 applications, including some CS and math programs not shown above. It took a TON of time and a good chunk of change, but I'm happy I did. If you had told me I could only send 6 applications, I definitely would have not included Berkeley, Harvard Stat, Harvard Biostat, Chicago, and UPenn. With that in mind, it was certainly a good investment. Fee waivers aren't very hard to get if money is a huge problem. Also, it doesn't seem to make much of a difference for your letter writers. They each submitted all of them in less than 30 min.

Even after you take the GRE and finish your essay, the process of looking for professors of interest, tweaking your essay to fit their prompt, and just filling out the application is surprisingly time consuming. For example, some schools wanted me to submit a list of all my relevant courses with the instructor, book, and brief summary provided for each one. You'll hear it again and again, but seriously, start early.

One of the main things I want to emphasize is that there is no prestige associated with my undergrad. At some places like Harvard, I was literally the only admitted student not from Ivy League, MIT, C9 League, etc. If any other admits find this post, they will immediately be able to identify me from that sentence alone. Don't count yourself out just because you don't attend a top undergrad.

Before I applied, I interacted with a few grad students who put an insane amount of effort into their applications. I compared myself to them and worried that I wasn't doing enough to get into top programs. You can spend a ton of time reading books on the application process, reaching out to multiple professors at each school, etc., but I'm not sure it will make much of a difference. As long as your essay is solid, your research, transcript, and letters are far, far more important.

Lastly, summer programs are a great way to get started with research. I tried a project with a prof early in my undergrad and was totally lost. After a few summer experiences, I had a publication and was able to start my own project. The applications are free, so you might as well apply over winter break and see what happens.

At the end of they day, it isn't complicated but it also isn't easy. Get great grades in hard classes and do research that produces concrete results. The letters will likely follow.

 

TL;DR: Apply to a lot of schools and don't worry about undergrad prestige. Also, attend summer programs.

Edited by Ryuk
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  • 2 weeks later...
Posted (edited)
Undergrad Institution: Big State School (TOP 30 US news  - Top 12 Statistics) 
Major(s): Double major, Statistics and Mathematics 
Minor(s): 

GPA: 3.9 
Type of Student: International Asian Male 

GRE General Test: Only submitted to Rochester 
Q:
 163 
V: 154 
W: 5.0 
GRE Subject Test in Mathematics:
M: n/a

TOEFL Score: n/a 

Grad Institution: n/a 
Concentration: n/a 
GPA: n/a 
Programs Applying: Biostatistics and Operations Research 
 
Research Experience: 2.5 years of experience in multiple wet/ dry labs, but nothing impressive.
Awards/Honors/Recognitions:  Phi Beta Kappa  
Pertinent Activities or Jobs:  TA for some Mathematics courses 
Letters of Recommendation: One from the chair of the department and 2 from the professors that I take graduate courses with 
Math/Statistics Grades:  
Math courses: Calculus I - III (A), Discrete Math (A), Linear Algebra (A-), Non-linear dynamics (A), Fourrier Analysis (A), Advanced Calculus (B), Combinatorics (B-), Complex Analysis (A)
Statisics courses (All A): Intro to Statistics, Intro to Biostatistics, Intro to Probability, Regression Analysis, Data Science, Stochastic Modelling (Undergrad), Intro to Optimizatiion (Undergrad), Mathematical Statistics, Machine Learning, Linear Programming (Graduate), Probability Theory / Measure Theory (Graduate), Stochastic Models in Operations Research (Graduate)
Computer Science courses: Intro to Programming (A), Object-oriented Programming (B+), Data Structures and Algorithms (A), Files and Databases (A)

Any Miscellaneous Points that Might Help: Take most of the first year graduate coursework and did well. Have good relationship with my professors. I used to attend mediical school before transferring to the US for college, so I put a heavy emphasis on this to draw connection with my current plan to pursue biostatistics.  My coursework is better alligned with OR, but I apply primarily to Biostatistics Program. I started off as pre-med  until Junior year so most of my earlier research experience was medical-related.  I also have taken a lot of biological / chesmitry courses due to this. 
 

Applying to Where: (Color use here is welcome)
PhD in Biostatistcs 
Michigan - Rejected - Accepted to MS/ PhD with no funding) 
JHU - Rejected
Minnesota - Rejected - Accepted to MS
Emory - Rejected - Accepted to MSPH
Duke - Rejected - Accepted to MS with 20k scholarship
Boston - Rejected - Accepted to MS
Penn - Rejected - Accepted to MS 
UC Davis - Rejected 
UT MD Anderson - Rejected
UT Houston - Accepted with no funding 
Brown - Interviewed - Waitlisted - Rejected 
Rochester - Interviewed - Waitlisted - Rejected 
Pittsburgh - Waitlisted - Accepted with fundiing 
 
PhD in Operations Research
Columbia - Waitlisted - Accepted to MS
Berkeley - Waitlisted - Accepted 
Georgia Tech - Accepted 
 
Other MS: 
Washington (Seattle) / Biostatistics - Accepted 
Harvard/ Biostatistics - Accepted 
CMU / Computational Biology -  Rejected from PhD, Accepted to MS
Georgia Tech/ Bioinformatics - Accepted
 
It was a very tough cycle for me. I applied to a wide array of programs. I am content with the result and very much appreciated those schools that chose to put some stocks on me. GRE was a very bad experience for me (took it twice). Except for the writing section, I struggled to do well in the other two. I think I am just in general not good as standardized tests. Those schools that interviewed me actually dug really deep into my essay as they asked me a lot of question about it. Since I did not have a solid mathematics background due to my earlier pre-med background, I did work hard on the essay, and I am glad that these schools appreciate that. 
 
I also underestimated the increasing competitive nature of biostatistics program, especially for international students. If I have to do it all over again, I may focus to apply to more OR / Statistics programs. Most biostatistics programs favor candidate with a MS under his/ her belt. To other future applicants, please be kind to your self! It is really mentally-taxing, but you will be fine! Sometimes taking a small step back is a big investment in the futue, so do not lost hope on yourself! 
Edited by BioStatKid
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Undergrad Institution: Top 200 US News
Major(s): Mathematics
Minor(s): Physics

GPA:  3.92
Type of Student: Domestic white male

GRE General Test:
Q:
 165 
V: 153 
 
Programs Applying: Statistics PhD programs
 
Research Experience: 18 months between two projects at my school. One paper submitted for publication, poster presentations at multiple conferences, patent pending for applied ML algorithm
Awards/Honors/Recognitions: Physics Honors Society
Pertinent Activities or Jobs: Tutor for 2 years, Pre-Calc TA for 1 year, Machine Learning intern at large company
Letters of Recommendation: All 3 were from professors who I am close with. 2 of them I did research with, and 1 was in charge of my tutoring/TA and taught a few of my classes. None of the three were statisticians.
Math/Statistics Grades: 
-Calc 1,2,3 (A, A, A)
-Differential Equations (A)
-Numerical Methods (A)
-Numerical Analysis (A)
-Linear Algebra (A)
-Intro to Statistics (A)
-Intro to Machine Learning (A)
-Real Analysis 1,2 (A, In Progress)
-Complex Analysis (A)
-Operations Research 1 (Graduate) (A)
-Probability Theory (Graduate) (In Progress)
-Information Theory (Graduate) (In Progress)

Applying to Where: All Stats PhD's
Colorado State - Attending / Admitted on 1/12, Offered TA position with ~$18,000/9 month funding
Columbia - Rejected
Duke  - Rejected
Harvard - Rejected
UCLA  - Waitlisted Rejected
Washington  - Waitlisted Rejected
Wisconsin - Rejected
Yale - Rejected
 
Reflection:
I guess I overestimated the quality of my app. I probably should've applied to some lower ranked schools, but getting waitlisted at some of the schools makes me think I was competitive and maybe in a non-covid cycle I would've gotten another acceptance. Not having any statisticians in my department, and not having any statisticians write a letter of rec probably didn't help my chances at top schools. I didn't think my GRE was too low for consideration, but thats also a possibility. I'm thrilled to have gotten an acceptance, although my advice would be to apply to a wider range of schools than you think, so that you'll have options.
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@moormath I think 20-40 rankings would've been your sweet spot, those top departments are hard to crack. Colorado State is a sweet department though and *the* place to be if you're interested in spatial stats, so congrats and glad it worked out for you!

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Posted (edited)

Well, I might have dun goofed my application. Not sure whether to reapply next year 

Here are my stats: 
 

Undergrad Institution: Average Canadian Uni. QS Rank of 560ish. ARWU of 400-500
Major(s): Applied Math
LOR: I might've really messed up by having poor letters (Using one history prof, an adjunct math prof who may have wrote me a lukewarm letter and one Assistant Prof who wrote me a great letter)
GPA:  3.76/4 (Math Courses Only)
Type of Student: Asian Male

GRE General Test:
Q:
 169
V: 166 
AWA: 5.5

Courses: 
Calc 1-3: A/A/B+
DE: B+ 
Stochastic Processes: A 
Math Stat 1: B
Linear Algebra I: A
Linear Algebra II: P

Extended Proofs: A
Stats 2: Pass
Data Analytics: A+

Regression Analysis: A
Elementary Probability: B+
Intro to Computing for Math and Stats: A+ 
Symbolic Computation: A+ 

Wondering if I should have taken a real analysis course and if that would have helped significantly?

Places I Applied To: Only Masters

Columbia University MA Stats: Waitlisted
Duke MS Statistical SciencesRejected
Berkeley MA Stats: Rejected
UofT MS Statistical Sciences: Rejected
UBC MS Stats: Rejected
UCLA Masters of Applied Stats: Accepted
UMich Masters of Applied Stats: Accepted
Cornell Masters of Applied Stats: Rejected
NYU Data Science: Accepted
Columbia Data Science: Rejected




I don't quite know how good my Statement is .

I also have absolutely no research.

Wondering if I should try reapplying next year? Wondering if my applicant potential maybe undervalued and there are some simple fixes and polish that could make me a more competitive applicant, especially if GREs are not waived in the 2022 cycle or if I'm basically punching my level. 

Thanks!
Edited by Joyboy
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5 hours ago, Joyboy said:

Wondering if I should try reapplying next year? Wondering if my applicant potential maybe undervalued and there are some simple fixes and polish that could make me a more competitive applicant, especially if GREs are not waived in the 2022 cycle or if I'm basically punching my level. 

Thanks!

I don't see why you would reapply next year unless you decide not to do a masters at all and to apply straight for PhDs next year instead. UCLA, UMich and NYU are all great universities, so if you still want to do a masters and you can afford to then I'd say to accept one of those offers this year.

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Well, I got a pretty good job offer this year and I'm wondering if I could end up getting into somewhere better given another year potentially. 

Thanks for the response!

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@JoyboyI agree that the programs you get into are fine, but yeah, if you have a good job lined up, go make some money, re-apply with some stronger letters and try to get a funded offer if you do end up going back to school.  I am a little surprised given your stats that you didn't get into a few more programs on your list.

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@bayessays Thanks a lot for the advice. I was thinking the same also. Do you like that a lack of Real Analysis, the B in Math Stat and relatively poor LORS, alongside with Covid and GRE waivers may have crippled my application for this year?

Thanks

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1 minute ago, Joyboy said:

@bayessays Thanks a lot for the advice. I was thinking the same also. Do you like that a lack of Real Analysis, the B in Math Stat and relatively poor LORS, alongside with Covid and GRE waivers may have crippled my application for this year?

Thanks

I don't think real analysis is necessary for MS programs, so I don't think that's a big factor, and one B should not have a big effect on admissions.  Not an expert in MS admissions though.  I think letters and SOP are the easiest thing to improve, as your GRE scores are great so I think you should be getting into good programs.  

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47 minutes ago, bayessays said:

I don't think real analysis is necessary for MS programs, so I don't think that's a big factor, and one B should not have a big effect on admissions.  Not an expert in MS admissions though.  I think letters and SOP are the easiest thing to improve, as your GRE scores are great so I think you should be getting into good programs.  

For master's programs in the US, real analysis won't matter that much and many people get in without having taken it. Most master's programs in the US are not very selective probably except for a few elite schools like Berkeley/Chicago/Stanford. However, statistics master's programs in Canada are much more selective because most of them are funded, and if you perform satisfactorily in the program then you are almost guaranteed to transfer into the PhD program. With that said, your lack of real analysis, low grades in a couple of statistics/math courses, along with your undergraduate institution might have made you less competitive at UBC/Toronto. Taking real analysis and obtaining good grades in them would definitely help your chances, and having a strong math background never hurts, especially if you consider a PhD in the future. However, even if you get strong grades in real analysis, UBC/Toronto are still gonna be reaches. It's just that admissions for top master's programs in Canada are very competitive. For example, UBC had 247 master's applicants in 2019 and admitted 15 of them. If you were to reapply, I would suggest also applying to schools at the level of Simon Fraser/Western/Alberta, which I think you have a good shot.

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  • 5 weeks later...
Too bored at work so thought of this post lol, but I do hope this to be helpful for people who have a different background.
Undergrad Institution: Canada Top 4 or 5 maybe
Major(s): Biochemistry
Minor(s): Statistics

GPA: cGPA 11.1/12 math/stat-related 11.6/12
Type of Student: Domestic Female Asian

GRE General Test:
Q:
 waived
V: waived
W: waived
GRE Subject Test in Mathematics:
M: waived

TOEFL Score: waived
 
Programs Applying: Biostatistics MS
 
Research Experience: 
- A bioinformatics thesis project (a year plus volunteered at the lab during summer, no pub, conference talk cancelled due to COVID) 
Awards/Honors/Recognitions:
- Entrance scholarship
Pertinent Activities or Jobs: 
- Introductory math course grading TA for one term (after submitting the applications, did mention in waterloo app tho)
Letters of Recommendation: thesis supervisor, program coordinator (lab course instructor), linear reg professor
Math/Statistics Grades:  
Intro to programming (python) - A-
Linear algebra - A
Calculus 1-3 - A+
Intro to modelling - A+
Intro statistics - A+
Intro prob - A+
Regression analysis - A+
Math stats - A-
Time series - A+

Any Miscellaneous Points that Might Help:
- got the SAS base/advance certificates

Applying to Where: Canadian Biostatistics MS only
UBC - Statistics MS (biostat concentration) / Rejected
Waterloo - Biostatistics MS / Accepted (Attending)
McMaster - Statistics MS / Pending on Jun 3rd 2021
Western - Epidemiology and Biostatistics MS (Biostatistics stream) / Rejected
Queens - Biostatistics MS / Accepted
U of T - Biostatistics MS / Accepted
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Undergrad Institution: Top 10 Private University
Major(s): Physics
Minor(s): Chemistry
GPA: 3.88/4.00
Type of Student: Domestic white male

GRE General Test:
Q:
 169
V: 169
W: 5.0

Grad Institution: Top 15 Public University
Concentration: Computer Science MS
GPA: 4.0/4.0
 
Programs Applying: Statistics PhD
 
Research Experience: One paper published in undergrad on biological optics. Two other research projects -- one on reinforcement learning (paper on arxiv), one on uncertainty quantification (still in progress when I applied).
Awards/Honors/Recognitions: A few merit scholarships; undergrad physics honor society; deans lists.
Pertinent Activities or Jobs: I took five years off between undergrad and the above MS in CS. During that time I taught high school math and completed a master's in teaching (3 years) and then worked for an education tech company (2 years).
Letters of Recommendation: One from a Biology professor, one from a researcher at Facebook AI Research (who was a physics postdoc when we worked together), and one from a Materials Science professor. I had done research with all of them. I think it was the first time any of them had written a rec letter for a statistics program.
Math/Statistics Grades:  Calculus Sequence (A's), Linear Algebra (A), Differential Equations (B), Analysis I (A), Complex Analysis (A), Numerical Analysis (A), Geometry (A), Probability (A), Stochastic Processes (A), Undergrad Math Stat (A), Linear Optimization (A), Nonlinear Optimization (A), Assorted CS courses (A's), Assorted Physics courses (A's, A-'s, and B+'s).
Any Miscellaneous Points that Might Help: N/A

Applying to Where: (All Stats PhD programs)
Duke - Accepted
NCSU - Rejected
UNC - Rejected
Harvard - Rejected
Penn State - Accepted
TAMU - Accepted
 
Thoughts: I don't have any super coherent thoughts, other than I'm totally satisfied with where I wound up (Duke)! I had a preference to be in North Carolina, and thought I'd have the best shot at NCSU over UNC or Duke, so the NCSU rejection was definitely disconcerting. But Duke was my top choice and I couldn't be more excited to start in the fall! I just wish I could have been a fly on the wall when these committees were reading my application haha. Really, I felt pretty good about my odds at all these schools other than maybe Harvard, but I guess my changing fields multiple times plus the random work experience in education may have generated mixed reactions (e.g., interesting/well-rounded vs. chaotic/unfocused)? Or maybe that's reading way too much into things, who knows
 
I guess I'd say at a philosophical level -- don't be afraid to aim high and put yourself out there, even if it's scary to change fields or go back to school. Two years ago, I had an ok job but knew I wanted more school at some point, so I figured what the hell and applied to some CS programs (despite my entire CS experience being one semester of intro to python). I got rejected by 7 out of 8 of them, but the one I got in was an awesome experience. This cycle, I felt way more confident, since I had waayyyy more relevant coursework under my belt plus some additional research and a more solid SOP, but I still had mixed results. So I guess just go for you want, roll with the rejections/acceptances (and expect both as a necessary part of life), and make the most of the opportunities you do get. And I'd say for grad apps specifically also cast a wide net, since there's a whole lot of randomness to the whole process. Good luck everyone!
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