2020 Applicant Profiles and Admission Results for Statistics/Biostatistics

[captivatingCA]

Past threads: 2013, 2014, 2015, 2016, 2017, 2018, 2019

Here's the thread to submit your profile and results for stat and biostat programs for Fall 2020. You only have an hour after you post to edit, so it is best to post only when you have all of your results or have made a decision. Give as much detail as you feel comfortable with!

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

[captivatingCA]

Undergrad Institution: ~Top 100 (according to US News)
Major(s): Mathematics
Minor(s): Computer Science
GPA: 3.85

Type of Student: Domestic Black Male

GRE General Test:
Q: 163(~85%)
V: 164(~90%)
W: 4.5 (~85%)
 

Programs Applying: Statistics and Biostatistics PhDs

Research Experience: 

• I did research during my freshman and sophomore years, but it wasn’t relevant to stats.
• I worked with a math professor at my university on a bunch of random stuff (e.g. data visualization) over the past two years. This wasn’t research per-se, mostly just learning the material in a more intimate setting.
• I did summer research programs after my sophomore and junior years. Both were in well-respected departments. One was in a stats department, and the other was in biomedical informatics.
• I worked in a stat professor’s lab when I was on exchange.

Letters of Recommendation: Mentors from my past two summers of research and a professor who I have taken a few courses from.

 

Math/Statistics Grades: Calculus II, III (A, A), Intro to Linear Algebra (A), Proofs and Problem Solving I, II (A, A), Differential Equations (B), Intro to Analysis I (A), Numerical Analysis (A), Probability and Statistics I, II (A, A)

CS Grades: Intro to Computer Science (A), Computer Science I (A), Computer Science II (A)

I spent a semester on exchange at a top 3 university (according to US News). Here are the relevant courses:

Modern Algebra I (A), Discrete Math (A), Essential Data Structures (A)

Applying to Where:
Harvard - Biostatistics PhD / Interview invite-1/7 / Accepted-2/11
NC State - Statistics PhD / Accepted-1/7
Texas A&M - Statistics PhD / Accepted-1/19
UW - Biostatistics PhD / Interview invite-1/24 / Accepted-3/4
Duke - Statistics PhD / Accepted-1/31
UW Madison - Statistics PhD / Accepted-1/31
UW - Statistics PhD / Accepted-2/7
UC Berkeley - Statistics PhD / Accepted-2/11
U Michigan - Statistics PhD / Accepted(funded Master's)-2/14
CMU - Statistics PhD / Accepted-2/21
Cornell - Statistics PhD / Accepted-2/24
UChicago - Statistics PhD / Waitlisted-2/26

Takeaways: I thought it would be good to share some of the things I've learned from this application process. I'll try to keep it short!

• First some straightforward, actionable advice. Apply for the NSF GRFP, it makes the rest of the application process so much easier. Study for the GRE; it's not hard but it's easy to get caught off-guard by some of the questions(at least it was for me). Turn in your applications early; it's a huge weight off your shoulders during a very stressful period.
• Trust your recommenders, advisors, and mentors. I applied to so many places because I was unsure of my chances at any of them. However, one of my recommenders told me at the beginning of the school year that I'd be successful in my applications. It's definitely important to hear multiple opinions, but if your advisor is experienced in the field, take their advice to heart.
• Don't compare yourself too much. Obviously the whole point of this thread is to compare yourself to others, just don't stress over it too much. GradCafe is great to see some of the commonalities between successful applicants. As long as you cover your bases though, missing one or two aspects that someone else had may not make as much of a difference as you think. Not to mention all of the factors you don't see on GradCafe.
• Don't give up if you didn't go to a brand-name school! I met lots of people on visits who didn't go to the Harvards and Stanfords of the world. There are other ways to stand out besides going to a big name school, so don't give up just because you go to Directional State U.

Hopefully someone finds this useful!

Edited March 21, 2020 by captivatingCA

[Fred210]

Undergrad Institution: (Three year college in Netherlands)
Major(s): Mathematics and Physics, double bachelor of science.
Minor(s): NA
GPA: 3.95 (Cum Laude)

Type of Student: Domestic (USA) male

GRE General Test:
Q: 170 (96%)
V: 161 (85%)
W: 5 (92%)
GRE Subject Test in Mathematics:
M: 800 (80%)

Grad Institution: UC Berkeley M.A. Statistics (1 year)

Concentration: Statistics
GPA: 3.95
 

Programs Applying: Statistics and Biostatistics Ph.D.

 

Research Experience:

1. Bachelor Thesis in Functional analysis and Quantum Mechanics, some original results proved.

2. Graduate student researcher position in Statistics (started after having applied to programs but was mentioned in application)

3. Various small projects in statistics and mathematics, both non-academic and academic.

Awards/Honors/Recognitions: Cum laude Bachelor
Pertinent Activities or Jobs:

1. Tutored for graduate level statistics and probability courses

2. Tutored for undergrad mathematics for biology course

3. Student chair of academic board at undergrad

Letters of Recommendation: From professors I've taken courses with in math and physics. I don't think they were very strong. Also, as a warning, europeans tend to write letters in a much more dry way than Americans. In some places, it is standard to actually write criticisms in the letter. I don't think this happened with me but I've heard such stories from people in admission committees.

Math/Statistics Grades:  (Took 40-50 courses in mathematics and physics)

Undergrad: Calculus 1,2,3 (A), Linear Algebra 1,2 (A),  Numerical Mathematics (A), Real Analysis (A), Probability Theory (A), ODE's (A), PDE's (A), Systems Theory (A), Dynamical Systems (A), Statistics (A), Asymptotic Statistics (A), Metric spaces (A), Measure and Integration (A-), Functional Analysis (A), Differential Geometry (A), Analysis on Manifolds (A), Data Science in Python (A), Computer Science in Python (A+), Complex Analysis (A)

Quantum Mechanics I, II (A), Advanced Mechanics (A), Quantum field theory (A), Group Theory (B+/A- ish) , Representation Theory in Physics (A)

 

Grad: Measure theoretic probability 1 and 2, Theoretical Statistics 1 and 2, Statistical Computing in R ,  Data Structures and Algorithms in Java 

Any Miscellaneous Points that Might Help:

My profile was strong (academically). At the time of applying (I had not yet completed the masters) , I didn't have as much relevant research experience nor did I have strong letters. It didn't help that because my masters was a one year program, I had to apply for the PhD programs immediately upon starting the masters. I thought that my profile was strong enough to make up for this. It was not. My take away is that strong letters are essential for the top programs. My profile is much stronger now and I will be reapplying next year. Last year when I applied to masters programs I was accepted everywhere except Stanford (including some Ph.D. programs in mathematics even though I applied to the masters). As a result, I did not change my application (essays etc) by much, thinking they were already good. I believe that this was a mistake and that my application was focused too much on my academic performance/aptitude and not enough on my research performance/aptitude. I did not apply to any Safeties since I had good reason to believe I would be accepted into one of the programs below.  Funny enough, the first response I got was being waitlisted at Stanford which, at the time, I took as a good sign. 
Applying to Where: (All Phd's)

School - Stanford University, Waitlisted (I.e. Rejection with honors)
School - UC Berkeley Statistics / Rejected
School - University of Washington, Seattle Statistics, Rejected
School - University of Washington, Seattle Biostatistics, Rejected

School - Carnegie Mellon Statistics, Rejected

School - Harvard Statistics, Rejected

School - University of Chicago Statistics, Rejected

School - John Hopkins Biostatistics, Rejected

 

Edited March 21, 2020 by Fred210

[Jasmine Ng]

Undergrad Institution: top 100 us new
Major(s): Mathematics 
Minor(s):Business Analytics
GPA: 3.7

Type of Student: International , Male

GRE General Test:
Q: 165 
V: 140 
W: 3.0 

 

Programs Applying: (PhD Statistics/ PhD Biostatistics)

 

Research Experience: 

Research Assistant for Economics professor (1 year) (same as data analysis)

Project in Applied Statistics (got funding for 1 semesters)

2 manuscripts allmost done

1 summer research at NCSU
Awards/Honors/Recognitions: Top 5 students for 3 years (awards total $10k), passed first 2 exams Actuary during freshman
Pertinent Activities or Jobs: Tutor for 8 semesters, 2 semesters holding 1 credit course

Letters of Recommendation: Strong letter of recommendation!!!

Math/Statistics Grades:  calculus sequence,  mathematical statistics sequences, intro to analysis, survival analysis, machine learning, bayesian, stochastic process, applied statistics sequences, DE, linear algebra, advance linear algebra, stats computing, stats consulting, probability and statistics sequences. 3 B otherwise A


Applying to Where: 
Accepted: Virginia Commonwealth University (Biostats), University of Cincinnati (Stats), Texas Tech (Math stats), University of Colorado (MS Biostats), Oklahoma State Uni (Stats) University of Mississippi (biostats), UC Riverside (MS stats), Michigan Tech Uni (stats)

Waitlisted:  Colorado State University (Stats)

Rejected: Uni Connecticut, Uni Georgia, Southern Methodist University, University of Missori (ALL STATS)

Edited March 21, 2020 by Jasmine Ng

[likewater]

Undergrad Institution: Top 10 USNWR (not known for grade deflation)
Major(s):  Cognitive Science
Minor(s):  Math
GPA:  3.96

Type of Student: Domestic, not getting any diversity points

 

Relevant Courses: (H) Linear Algebra(A-), (H) Multivariable Calculus (A-). Fall Term: (H) Real Analysis (A), (H) Probability (A)

Less Relevant Courses: Intro to programming (A), Data Structures (A), Social Network Analysis (A), Human-Computer Interaction (A)

GRE General Test:
Q: 169
V: 157
W: 5.0
 

Programs Applying: Biostatistics PhD programs

 

Research Experience: About a year's worth of research on sentence processing, no publications
Awards/Honors/Recognitions: None outside of GPA related stuff.
Pertinent Activities or Jobs: TA for calculus sequence

Letters of Recommendation: Cog Sci prof I'm doing research with (Allegedly strong), linear algebra prof (Strong but not glowing), SIBS professor (Allegedly strong)

Any Miscellaneous Points that Might Help: Attended SIBS

Applying to Where:
Harvard - Rejected
University of Washington - Rejected
Johns Hopkins - Rejected

UNC - Accepted, ~25k funding
Michigan - Rejected from PhD / Accepted into Masters, ~25k funding
Minnesota - Accepted, ~26.5k funding + 5k for the first year
UCLA - Accepted, ~24k funding
Brown - Rejected from PhD / Accepted into Masters, 50% tuition scholarship

Berkeley - Rejected
Duke - Rejected
Columbia - Rejected
UPenn - Rejected
Emory - Rejected
Rutgers - Rejected
Boston University - Waitlisted / Rejected

Thoughts:

All in all pretty happy with how applications went, given that I took my first math course last year. Only one school ended up asking for my fall grades explicitly (Michigan) despite me taking pretty important courses during the fall, although I did send updated transcripts to schools that had ways of doing so. The sentiment about there being no such thing as safeties and rankings/ease of admissions not being 1-1 seems to be accurate. My only tip for future applicants is to get the hell off this website lol, it is super bad for the mental. Excited for the fall :).

[kingsdead]

Undergrad Institution: LAC, considered one of the "top" ones.
Major(s): Math
GPA: 3.74

Type of Student: Domestic Asian male

GRE General Test:
Q: 170 (96%)
V: 166 (97%)
W: 5.0 (92%)
GRE Subject Test in Mathematics:
M: 820 (81%)
 

Programs Applying: Statistics/Biostatistics PhD programs

 

Research Experience: 

• REU in math after junior year. Resulted in two (very standard undergraduate type) publications.
• Honors thesis during senior year in number theory. No publications.
• Research data analyst for ~8 months at the global health department of a university. Work resulted in two conference posters.

Awards/Honors/Recognitions: Award for applied math/teaching from my college, graduated with honors from department, standard GPA type stuff but nothing fancy.

Pertinent Activities or Jobs: 

• Tutor/TA for Calculus, Topology, Linear Algebra, Partial Differential Equations.
• Research data analyst for ~8 months at the global health department of a university. Did fairly basic data cleaning and analysis, used a lot of R and SQL. I think that this helped allay fears regarding my poor CS grades.
• Math tutor (part time) after graduating.

Letters of Recommendation: Math professor with whom I did REU research and thesis, math professor who taught measure theoretic probability, PI from data analyst job. Assume that all were solid but not spectacular.

 

Math/Statistics Grades:

• Math (All A or A+ unless otherwise stated): Multivariable Calculus, Linear Algebra, Discrete Math, Real Analysis, Abstract Algebra (basic groups/rings/fields), Topology, Number Theory, Complex Analysis, Combinatorics, Algebraic Number Theory, Homological Algebra (A-), Differential Geometry, Harmonic Analysis, Representation Theory (A-), Asymptotic Analysis, Commutative Algebra, Measure Theoretic Probability, Partial Differential Equations.
• Stats: Standard calc-based intro stats course (A-)
• CS: Intro CS (A-), Data Structures (B-), Algorithms (B+), Theory of Computation (A-)

Any Miscellaneous Points that Might Help: Peace Corps Volunteer – taught in a rural school, involved in other projects as well including some HIV/AIDS related programs for youth.

Applying to Where:

Biostatistics (All acceptances with funding):

Harvard - Rejected
University of Washington - Accepted
Johns Hopkins - Accepted
Minnesota - Accepted
UNC - Accepted
Berkeley - Accepted
Columbia - Accepted

Statistics:

Columbia - Rejected
Chicago - Waitlisted

Post-mortem:

• There is definitely randomness involved. In my opinion there are folks on this site (e.g. earlier posters on this thread) with stronger applications who did not get into some of the programs I got into. It's tough to say until you apply, so as long as you have some chance, just go for it.
• I think that my volunteer experience helped make my application stronger, or at least a little more interesting, based on how my interviews went. So if you have a somewhat unusual background or experience, don't be afraid to let that shine in your essays/interviews, as long as you can relate it organically to the rest of your application.
• I didn't attend any interview events – did all of them online or over the phone instead, and this didn't hurt my applications, so don't lose sleep if you aren't able to attend these sort of things!
• Seems that a few bad grades, even in related areas such as CS, can be offset by strengths in other areas and evidence that you have shored up those deficiencies (e.g. my bad CS grades being offset by my work experience as a data analyst).

That's all I got for now! Thanks everyone for all the help.

Edited March 26, 2020 by kingsdead

[SPIWizard]

Long-time lurker here. Don't usually have much to add to the discussion about PhD programs, I am applying only to Canadian masters programs. 

 

Undergrad Institution: Regionally prominent Canadian school (not Toronto, UBC, McGill or Waterloo)
Major(s): Statistics
GPA: 3.97 converted

Type of Student: Domestic (Canadian)

GRE General Test: Did not take
 

Programs Applying: Masters in Statistics

 

Research Experience: One USRA (aka. Canadian REU) working on computational statistics at home institution. One 2nd author paper in one of the big ML conferences.  

Awards/Honors/Recognitions: Dean's list, some GPA-based scholarships.

Pertinent Activities or Jobs: High school math tutor, worked as an financial analyst intern almost every summer (excel stuff). 

 

Letters of Recommendation: Strong letter from assistant prof who was my advisor (I was able to see this letter), two good letters from senior profs, well respected in Canada.

 

(Relevant) Math/Statistics Grades:  Calc I-III, two terms of linear algebra (applied topics, but proof based), two terms of non measure probability, two terms of real analysis, intro to math stats, experimental design, time series, linear models, a few statistics grad courses: stochastic analysis, bayesian stats, GLMs, high dim. statistics. 

Any Miscellaneous Points that Might Help: Nearly 10 courses in Economics, which mostly served to convince me that I was not into Econ.

 

Applying to Where: 
University of British Columbia - Accepted 

McGill University - Accepted 

University of Waterloo - Accepted 

Simon Fraser University - Rejected 

 

Notes:

• I hope this will help people who were in my position back in October. There are limited resources out there for domestic applicants in Canada, which makes sense given that even my own departments grad students are >50% international. 
• The offers are all funded, with funding a little lower than average PhD stipends. 
• I did not think my math background was sufficient to apply directly to PhD programs in the States, and hence did not take the GRE. 

Looking forward, or perhaps dreading, to be back for the PhD cycle soon... 

Edited March 26, 2020 by SPIWizard

[statsphd2020]

On 3/20/2020 at 11:33 PM, captivatingCA said:

Undergrad Institution: ~Top 100 (according to US News)
Major(s): Mathematics
Minor(s): Computer Science
GPA: 3.85

Type of Student: Domestic Black Male

GRE General Test:
Q: 163(~85%)
V: 164(~90%)
W: 4.5 (~85%)
 

Programs Applying: Statistics and Biostatistics PhDs

Research Experience: 

• I did research during my freshman and sophomore years, but it wasn’t relevant to stats.
• I worked with a math professor at my university on a bunch of random stuff (e.g. data visualization) over the past two years. This wasn’t research per-se, mostly just learning the material in a more intimate setting.
• I did summer research programs after my sophomore and junior years. Both were in well-respected departments. One was in a stats department, and the other was in biomedical informatics.
• I worked in a stat professor’s lab when I was on exchange.

Letters of Recommendation: Mentors from my past two summers of research and a professor who I have taken a few courses from.

 

Math/Statistics Grades: Calculus II, III (A, A), Intro to Linear Algebra (A), Proofs and Problem Solving I, II (A, A), Differential Equations (B), Intro to Analysis I (A), Numerical Analysis (A), Probability and Statistics I, II (A, A)

CS Grades: Intro to Computer Science (A), Computer Science I (A), Computer Science II (A)

I spent a semester on exchange at a top 3 university (according to US News). Here are the relevant courses:

Modern Algebra I (A), Discrete Math (A), Essential Data Structures (A)

Applying to Where:
Harvard - Biostatistics PhD / Interview invite-1/7 / Accepted-2/11
NC State - Statistics PhD / Accepted-1/7
Texas A&M - Statistics PhD / Accepted-1/19
UW - Biostatistics PhD / Interview invite-1/24 / Accepted-3/4
Duke - Statistics PhD / Accepted-1/31
UW Madison - Statistics PhD / Accepted-1/31
UW - Statistics PhD / Accepted-2/7
UC Berkeley - Statistics PhD / Accepted-2/11
U Michigan - Statistics PhD / Accepted(funded Master's)-2/14
CMU - Statistics PhD / Accepted-2/21
Cornell - Statistics PhD / Accepted-2/24
UChicago - Statistics PhD / Waitlisted-2/26

Takeaways: I thought it would be good to share some of the things I've learned from this application process. I'll try to keep it short!

• First some straightforward, actionable advice. Apply for the NSF GRFP, it makes the rest of the application process so much easier. Study for the GRE; it's not hard but it's easy to get caught off-guard by some of the questions(at least it was for me). Turn in your applications early; it's a huge weight off your shoulders during a very stressful period.
• Trust your recommenders, advisors, and mentors. I applied to so many places because I was unsure of my chances at any of them. However, one of my recommenders told me at the beginning of the school year that I'd be successful in my applications. It's definitely important to hear multiple opinions, but if your advisor is experienced in the field, take their advice to heart.
• Don't compare yourself too much. Obviously the whole point of this thread is to compare yourself to others, just don't stress over it too much. GradCafe is great to see some of the commonalities between successful applicants. As long as you cover your bases though, missing one or two aspects that someone else had may not make as much of a difference as you think. Not to mention all of the factors you don't see on GradCafe.
• Don't give up if you didn't go to a brand-name school! I met lots of people on visits who didn't go to the Harvards and Stanfords of the world. There are other ways to stand out besides going to a big name school, so don't give up just because you go to Directional State U.

Hopefully someone finds this useful!

May I ask where you choose to go out of these schools and how you decided?

[captivatingCA]

3 hours ago, statsphd2020 said:

May I ask where you choose to go out of these schools and how you decided?

I haven't decided just yet, though I've narrowed it down a good bit. I started with more obvious things like location and research fit, and used visits (in-person and virtual) to get a better sense of the departments. I also talked to people who know me well about my choices. I feel like most of it is based on personal preference not objective fact since all of these schools are great places to be.

I don't want to clog up the results thread, but feel free to message me if you'd like to know more.

[Casorati]

Undergrad Institution: One of UBC, Toronto, Waterloo
Major(s): Math/Statistics
Minor(s):
GPA: High 80s, 90+ in math/stat courses

Type of Student: International Asian Male

GRE General Test:
Q: 170 (96%)
V: 153 (60%)
W: 3.5 (39%)
GRE Subject Test in Mathematics:
870 (89%)

TOEFL Score: Waived

Grad Institution: Same school

Concentration: Statistics
GPA: ~90
 

Programs Applying: Statistics/Biostatistics PhD

 

Research Experience:  Part time RA with an assistant professor during undergrad. Graduate RA resulting in a master's thesis. Both related to causal inference. Paper submitted to Statistics in Medicine.

Awards/Honors/Recognitions: Nothing major.
Pertinent Activities or Jobs: TA for undergrad statistics courses

Letters of Recommendation:  One from my master's supervisor (associate prof), one from a senior prof who I took grad math stat with. One from an assistant prof whom I did my undergraduate research with.

Math/Statistics Grades:  Calculus 1-3 (A+;A+;A+). First year Algebra (A+). Linear Algebra 1-2 (A+;A+). ODE I (A+). Intro to Prob (A+). Intro to Statistics (A+).  Real Analysis I (A-). Real Analysis II (A-). Measure Theory I (A+). Abstract Algebra (B+). Complex Analysis (A+). Mathematical Statistics I (A+). Mathematical Statistics || Casella & Berger (A+). Graduate Statistical Inference (A+). Applied Probability (A+). Stochastic Processes (A+). Applied Linear Models (A-). GLM (A). Time Series (A). Experimental Design I (A+). Experimental Design II (A+). Survival Analysis (A). Missing Data and Causal Inference (A+)

Applying to Where: 

 

Biostatistics PhD:
Pennsylvania - Rejected
Michigan - Rejected

UCLA - Rejected

McGill - Accepted

Minnesota - Rejected

UNC - Waitlisted

Florida - Pending

Johns Hopkins - Rejected

Berkeley - Rejected

 

Statistics PhD:

Wisconsin - Rejected

Stanford - Rejected

UBC - Accepted

Penn State - Rejected

UIUC - Rejected

Toronto - Rejected

Waterloo - Accepted

Wharton - Rejected

 

Some take-aways:

The competition among international students has gotten very stiff in recent years. I got accepted into 3 Canadian schools I applied but got rejected across the board for US schools. I imagine that my Canadian background was looked upon favourably during admission at UBC/McGill/Waterloo. However, it appears that even for tie-2 schools like Penn State/UIUC/UCLA, the bar for international students to get in is still very high. This may have something to do with the current political climate in the US as many schools are restricting the number of international students that can enroll. With that said, there are some very strong programs in Canada or even Europe that you can consider. These programs have strong faculty members consistently publishing in top journals as well as solid placements records. If you look at UBC, the placement data indicate that over half of their graduates ended up with a faculty position, which is better than some of the tie-2 programs in the US. I encourage future applicants to look into Canadian schools as well. If you do well in these programs, you will be in a very good shape in academic market after graduation.

[Stochastics]

Undergrad Institution: Medium Sized Liberal Arts School
Major(s): Combined BS/MS

                  Bachelors: Mathematics & Statistics

                  Masters: Statistics
Minor(s): Actuarial Science
GPA:  Bachelors: 3.94/4.0 

           Masters: 4.0/4.0

Type of Student: Domestic, Male

GRE General Test:
Q: 163 (82%) <- in retrospect would've practiced more
V: 161 (88%)
W: 4.0 (57%)
 

Programs Applying: Statistics/Operations Research

 

Research Experience: Presentation at JSM 2019, research article to be submitted soon.
Awards/Honors/Recognitions: Scholarships from the math and statistics departments.
Pertinent Activities or Jobs: Was a TA for Regression and Statistical Inference.

Letters of Recommendation: Strong, but not from anyone well-known.

Math/Statistics Grades:  Calculus III (A),  Linear Algebra/Proofs Course (A), ODE (A), Probability (A+), Optimization (A), Abstract Algebra (A-), Real Analysis (B+), Measure Theory (A), Casella-Berger (2 courses, A's in both), Regression (A), Time Series (A+), Bayesian (A), DOE (A), Random Programming Courses (A's), Stochastic Processes (A), Consulting Course (A), Biostatistics/Survival Analysis (A), GLM (A), Nonparametric Statistics (A).
Any Miscellaneous Points that Might Help: Interested in Time Series, Stochastic Processes, MCMC, general probability topics. Had internships in the finance and oil industries.

Applying to Where: 

 

Statistics:
University of Chicago - Rejected 
Columbia University - Rejected 
Purdue University - Admitted

Michigan State University - Admitted

University of Michigan - Rejected

Ohio State University - Admitted

Texas A&M University - Admitted

 

Operations Research:

Cornell University - Rejected

Georgia Tech - Admitted

[figuringitout1]

Undergrad Institution: Big State School
Major(s): Statistics and Mathematics 
Minor(s): n/a
GPA: 3.758

Type of Student: Domestic Female 

GRE General Test:
Q: 161 (76%)
V: 153 (60%)
W: 4.5 (81%)

(not great under pressure) 

GRE Subject Test in Mathematics:
M: n/a

 

Programs Applying: Biostatistics Masters 

 

Research Experience: SIBS Program, but nothing else  
Awards/Honors/Recognitions: STEM scholarship, nothing major 
Pertinent Activities or Jobs: Math Grader

Letters of Recommendation: Professor for two of my stat courses (knows me pretty well), instructor from SIBS (worked on research project together), mentor from STEM scholarship (knows me extremely well, but not in stat). 

Math/Statistics Grades: Calc I (AP), Calc II (B+), Vector Calc (A), Statistical Methods I and II (A, A),  Linear Algebra (B+), Probability (B), Math Stat (B), Intro to  Experimental Design (A), Transition to Adv. Math (A), Vector Analysis (A), Algebraic Structures (C), Theory of Statistical Inference (B), Computing in Statistics (A), Big Data Analytics (A), Analysis (B), and Ordinary Differential Equations (A) 

(Also have 2 transfer courses in biostat from SIBS program both with A's)

Any Miscellaneous Points that Might Help: Graduating a year early

Applying to Where: 

Duke - Masters, Admitted, $25,000/year 
Colorado Denver - MS, Admitted, no funding
UNC - MS, Admitted, funding not announced yet
Boston - MA, Admitted, $15,000 (total)
Emory - MSPH, Admitted, $15,000 + $10,000 in work study (total)
Tulane- MS, Admitted, $10,000/year

Berkeley- MA, Rejected
Brown- ScM, Waitlisted 

[noinim]

Undergrad Institution: Top LAC
Major(s): Mathematics 
Minor(s):
GPA: 3.88 (major GPA like 3.92 ish)

Type of Student: Domestic Asian Woman

GRE General Test:
Q: 167 (90%)
V: 170 (99%)
W: 6.0 (99%)
GRE Subject Test in Mathematics:
M: N?A

TOEFL Score: N/A
Grad Institution: N/A
 

Programs Applying: (Statistics/Operation Research/Biostatistics/Financial Math/etc.)

 

Research Experience: REU in CS/ML (no publications), senior thesis with honors in applied stats/ML/probability theory 
Awards/Honors/Recognitions: School GPA awards, mathematics department awards
Pertinent Activities or Jobs: TA for linear algebra, real analysis, took 1 year after college to work in consulting

Letters of Recommendation: 3 from undergrad math professors. All 3 I took multiple classes with, TA'd for, and/or did research with

Math/Statistics Grades: Calculus sequence, linear algebra, real analysis 1, abstract algebra, advanced linear algebra, a smattering of other mid-level courses (diffeq, number theory, combinatorics, etc.), probability theory, stats theory, computational stats, intro CS, fundamentals of CS, data structures, intermediate macro+micro, econometrics. All A or A+, except abstract alg (B+), fundamentals of CS (B+), data structures (A-), diffeq (A-), linear alg (A-)
Any Miscellaneous Points that Might Help: 

Applying to Where: (all stats PhD unless otherwise mentioned, in rough order of notification) 
University of Minnesota - Accepted (Declined)

Duke - Accepted (Declined)

Harvard - Rejected

University of Michigan - Accepted (Declined)

UCLA - Accepted (Declined)

Carnegie Mellon (Joint Stats & Public Policy) - Accepted

MIT (Social Systems & Engineering)- Accepted

UW - Ghosted  :(( i.e. prob rejected at this point

Because I was interested in social networks, policy, and economics applications, I also applied to some demography programs with close ties to ML/stats, but that's probably a bit far afield. 

 

Notes: 

• It was a definite gamble to essentially apply only within the top 30, but my reasoning was that I had a job already, there were no such thing as guaranteed safety schools for PhD apps, and I didn't want to apply to any place that didn't have a relatively strong investment in doing interdisciplinary social science & stats/ML research (and that happened to be departments that were more highly ranked and more established). Also, looking at previous results, it does seem like domestic students have a small boost in admission outcomes, which I took into account when I was applying. 
• I think doing a CS REU was helpful to offset my relatively lower grades in CS.
• I didn't plan for this entirely, but it turned out that I took a bunch of classes with the same 3 professors in undergrad, and got to know them quite well both in class and in other capacities (as a TA, academic advisee, research advisee, etc.) and I think this definitely helped my app a lot. So get to know your professors well! and if you're applying after graduating, make sure to stay in contact and let them know before you graduate that you may be applying to grad schools if you can
• A lot of people warn not to read gradcafe too much, and I remember it was definitely painful to watch admissions results roll in and be refreshing an empty inbox (there was like a span of 5 days when my top 3 favorite schools Harvard, UW, and CMU all came out and I had gotten none of them at that point) but it was also comforting to read yall's commiserations in the main forum thread. So thanks for keeping me company these past few months haha

 

 

[icantdoalgebra]

Undergrad: UC Berkeley

Major: Computer Science

GPA: 3.96 (4.00 major gpa)

Student Type: Domestic, Asian Male

GRE:

168V(98)/170Q(96)/5.5W(98) (percentiles might be off)

Math Subject: 840 (84)

Courses: Honors Linear Algebra (A+), Honors Abstract Algebra (A), Honors Real Analysis (A-), Honors Complex Analysis (A+), Numerical Analysis (A+), Grad Analysis I and II (A, A), Probability Theory (A+), Mathematical Statistics (A+), Theoretical Statistics I, II (for PhD Students, A, A), Probability for PhD Students (A-), Intro to Programming (A), Data Structures (A), Discrete Math and Probability (A+), Intro Computer Architecture (A), Databases (A), Algorithms (A), AI (A), Machine Learning (A)

Programs Applying: Stats PhDs

Research Experience: Currently working with a professor and his students on Bayesian nonparametrics, trying to wrap it up and publish soonish (likely second author, contributed some theoretical and numerical results), also working with another professor on more applied machine learning research, writing code to implement it as well as other potential modifications and applying it to more data

Work Experience: Spent a summer at a startup doing some natural language processing, another summer at a quantitative asset management firm

Letter of Recommendation: Professor doing research with (hopefully would be decent, but met him twice in person in the past 6 months), another professor that I took Theoretical Statistics with (will also hopefully be decent as I think I stood out a decent amount in that class, actively participating and going to office hours), and the third professor is the also the one I'm doing research with (but I've met with them once)

Results:

• Stanford: Waitlisted
• UC Berkeley: Haven't heard back, talking to some people on the inside, seems like a waitlist
• Harvard: Rejected
• UW: Ghosted, likely rejected
• Chicago: Waitlisted
• CMU: Accepted 
• Duke: Accepted 
• Michigan: Accepted 
• NCSU: Accepted (Declined)
• Columbia: Rejected

Miscellaneous Points: I think Duke was really interested in the research I did and that probably helped me out a lot. The main boosts to my application are probably taking a lot of hard math classes, as well as the PhD statistics classes at Berkeley, and doing research with some pretty big names in the field. My main failings probably came from the fact that its fairly hard to establish connections with professors as an undergraduate at Cal, and after trying to get involved in research for about 5 semesters straight I only managed to get it the semester when I was applying to PhD programs.

Best of luck to anybody reading this from the future who are also applying!

[hcms1]

Undergrad Institution: The City University of New York
Major(s): Math
Minor(s):
GPA: 4.00

Type of Student: Domestic Male

GRE General Test:
Q: 166 (89%)
V: 164 (94%)
W: 4.5
 

Programs Applying: Biostatistics, Statistics, and Data Science master's programs

 

Research Experience: 1 year of research in economics
Pertinent Activities or Jobs: 1 year work experience as Data Analyst at a healthcare company

Math/Statistics Grades:  A or A+ in all courses

Letter of Recommendation: 3 letters total; 1 each from an epidemiology professor, a statistics professor, and a math professor.
Any Miscellaneous Points that Might Help: I had a github portfolio with some python and R data analyses. Fairly simple stuff. Nothing too fancy.

Applying to Where: (all are MASTER'S programs)
Harvard - Health Data Science:  Admitted
Harvard - Data Science: Rejected
UWashington, Seattle - Biostatistics: Admitted

UMass, Amherst - Statistics: Admitted

Stony Brook - Statistics: Admitted

Boston University - Biostatistics: Admitted

Uni. of Toronto - Biostatistics: Admitted

Brown - Biostatistics: Admitted

UCSD - Biostatistics: Admitted

UMichigan, Ann Arbor - Biostatistics: Admitted

Edited April 3, 2020 by hcms1

[DanielWarlock]

GRE: 166 (Verbal), 168 (Math)

GPA: 3.92 (UofT Engsci undergrad), 4.00 (Harvard CSE master)

Quant GRE: NONE

Research: Monte Carlo, Markov Chain theory

Publication: NONE

Courses: Took graduate probability and inference at master; not much advanced math classes

Recommendation: strong letters, profs know me well. 

Admit: harvard, berkeley, duke

Rejection: University of Florida, University of Minnesota Twin Cities, Columbia University in the City of New York, Wharton School of the University of Pennsylvania etc.

Decision: I will remain at Harvard even though Berkeley seems to be a better place to go with more "big names". This choice is personal because I know Harvard better and it suits me well so far.

Advice: I think it is more important for one to focus on thinking and problem solving than worrying too much about the institution they will be affiliated to.

Contact: you can contact me with yufan_li@g.harvard.edu if you have any questions about application or would like to collaborate on a research project/problem.

This forum has been helpful. Thanks!

 

 

 

[nat_1421]

Undergrad Institution: Large State School (Top 40)
Major(s): Statistics, Math
Minor(s): Computer Science
GPA: 3.91

Type of Student: Domestic White Female

GRE General Test:
Q: 166
V: 158
W: 4.0
GRE Subject Test in Mathematics: N/A

 

Programs Applying: Biostats Masters

 

Research Experience: 2 years in non-stat field. no publications, but got promoted and managed 2 other student researchers
Awards/Honors/Recognitions: Phi Beta Kappa, department scholarships, Dean's List, President's List
Pertinent Activities or Jobs: Research assistant, private tutor

Letters of Recommendation: 1 math prof, 1 (non tenure) stat prof, and my research PI 

Courses:  Calc III (A-), Honors Linear Algebra (A-), Spaces & Functions (pre-req real analysis, A), Intro Stats (A), Regression (A), Intro Math Stats I, II (A), CS 1 (A), Discrete Math (A), CS 2 (A-)

Senior year classes without grades: Math Stats I & II, Bayesian Stats, Numerical Analysis, Algorithms, Real Analysis, Optimization

Applying to Where: (Master's biostats)
Harvard - Admitted / 60 credit
Washington - Admitted / Capstone Track
UNC -  Admitted

Michigan -  Admitted

Minnesota -  Admitted

Wisconsin - Admitted

Penn -  Admitted

Iowa -  Admitted

Boston U  -  Applied Biostat / Waitlisted

 

I'm planning on either attending Wisco or Harvard. My big takeaways/things I'd do differently from this process were: 

-Worry less about the SOP 

-Figure out which programs *actually* give funding to master's students 

-Apply to a mix of biostat & stat programs

-Apply to some PhD programs (maybe)

[cl27]

Undergrad Institution: University of Pittsburgh
Major(s): Microbiology
Minor(s): Chemistry, Neuroscience, Computer Science, Economics
GPA: 3.73

Type of Student: Domestic Asian Female

GRE General Test:
Q: 170 (96)
V: 163 (93)
W: 5.5 (98)
 

Programs Applying: Biostatistics

 

Research Experience: Summer internship at NCBI, ~8 months computational biology undergrad research, some research at current position (3 years)
Awards/Honors/Recognitions: Magna Cum Laude, Phi Beta Kappa, attended on a full scholarship
Pertinent Activities or Jobs: 3 years clinical lab and research experience

Letters of Recommendation: Calculus professor, economics professor, director of institute at NIH

Math/Statistics Grades:  Calc I (high school), II, III, Linear Algebra, AP Stat (high school) (all A's, didn't take math classes in college so had to take some after)
Any Miscellaneous Points that Might Help: Really big lack of stats experience but I made sure to have at least the minimum prerequisites and I think I've shown through grades/test scores that I'm capable of succeeding in higher level math classes. I figured out about a year out of undergrad that I wanted to pursue biostats, then spent 2 years catching up on math classes at community college. I also have a decent amount of research experience even though it's not it statistics and I don't have any papers. I also think having a computer science minor was helpful because even though I don't have stats experience I think I can pick up the stats programming pretty fast. I applied to all PhD programs since many consider you for a Master's anyway, so why not try to get paid! I probably shouldn't have bothered applying to UW, Hopkins, and Harvard, but it doesn't hurt (except for a few hundred dollars).  

Applying to Where: 
University of Washington - Biostatistics - Rejected
Harvard - Biostatistics - Rejected
Johns Hopkins - Biostatistics - Rejected

New York University - Biostatistics - Rejected

University of Pittsburgh - Biostatistics - Rejected (PhD) Accepted (MS) no funding

Boston University - Biostatistics - Rejected (PhD) Accepted (MS) no funding

Emory University - Biostatistics - Rejected (PhD) Accepted (MS) possible work study

Duke University - Biostatistics - Rejected (PhD) Accepted (MS) 20k/yr

University of Colorado - Biostatistics - Rejected (PhD) Accepted (MS) likely funded after 1-2 semesters

University of Minnesota - Biostatistics - Rejected (PhD) Accepted (MS) possible funding (never heard more)

Vanderbilt University - Biostatistics - Accepted (PhD) - fully funded 32k/yr stipend - woohoo!! They only accept 4 per year so this was a big surprise

University of Florida - Still haven't heard - UF you should make your decisions earlier in the season...

 

Honestly, coming in I didn't know anything about these programs and didn't realize that most people come from statistics backgrounds, and many applying for PhDs already have a master's in biostats or stats. If you're coming from a science background, it is possible!! I definitely got lucky...thanks to all who declined Vanderbilt!

[SomeNerd]

Undergrad Institution: US Big State ~150 US News Math&Stats Dept
Major(s): Mathematics
Minor(s): Computer Science, Actuarial Science
GPA: 3.85

Type of Student: International Female 

GRE General Test:
Q: 168 (93%)
V: 153 (60%)
W: 3.5 (39%)
GRE Subject Test in Mathematics:
M: N/A

TOEFL Score: N/A

Grad Institution: N/A

Concentration: N/A
GPA: N/A
 

Programs Applying: Statistics

 

Research Experience: My school: 1) 1.5 years in engineering (some data science work), a 3rd author published IEEE conference paper, a 2nd author submitted 2) 1.5 years in atmospheric science, international conference presentation (poster). Other school: summer REU in biostatistics and statistical genetics in a small private college, 3rd author published conference paper, 2 oral presentations.
Awards/Honors/Recognitions: school/dept scholarships every year in undergrad
Pertinent Activities or Jobs: tutor for 1 summer

Letters of Recommendation: 3 rec letters from all 3 advisers of research mentioned above. #1,2 not in the field of stats, #3 could be known by some dept, but not big name

Math/Statistics Grades:  all A's in Calculus sequence, real analysis sequence, mathematical statistics sequence, differential equations sequence, mathematical proof
Any Miscellaneous Points that Might Help: got an A- in a graduate level numerical analysis class, not really related to statistics though. Was taking a graduate intro-level mathematical statistics when applied

Applying to Where: 
Accepted: Ohio State University, Colorado State University, Baylor University, My undergrad department

Rejected: North Carolina State University, University of Michigan, University of Texas Austin, University of Pennsylvania

Still don't know what's going on...probably waitlisted/future rejection: University of North Carolina Chapel Hill, Texas A&M University, Rice University, University of Florida

 

Some reasoning behind picking the schools I picked:

As you can tell, I really had no idea where I would end up. Average GRE and not top undergrad school definitely brought a lot of uncertainty to me. So I applied to a wide range of top/middle/low ranking schools, and big/small depts. I don't mind big cities nor small towns, but I did try to avoid west coast and New York b/c cost of living, and avoided most midwestern schools b/c I don't like brutal winters. Also, quite obviously, I tried to stay in Texas (applied to 5 Texas schools), but it seems they don't fit me.

 

Interesting fact for those who are from a nowhere-close-to-top school:

A girl that I am friend with (from same undergrad institution), had no research experience, but she's a top student, got accepted to UNC. No big name letters of rec either. So there are still chances here if you have your undergrad from a nowhere-close-to-top school and have no research experience.

 

Side note:

I think my research and good grades in math class weigh the most. Although my research is all over the place (from my naive attempts in other fields before committed myself to stats), and no 1st author publication, but they did at least bring me good letters of rec from the professors I worked with. 

[shuggie]

Undergrad Institution: Regional School. Not well known or regarded, but on a shared campus with a more known school.
Major(s): Mathematics
Minor(s): Computer Science
GPA: 3.63

Type of Student: Domestic White Male

GRE General Test:
Q: 166 (89%)
V: 157 (76%)
W: 4.0 (56%)
 

Programs Applying: (Statistics and one Biostat.)

 

Research Experience: One year long funded research project (~20hrs a week) in conjunction with a local non profit with focus on time series modeling. A summer research project on estimation theory that resulted in a presentation at JSM. Not really research but did an extra credit project for Real Analysis that also resulted in a conference talk at MAA MathFest. Some later work I did for a course got presented at JSM 2019 but I couldn't make it (still on my CV). 

Awards/Honors/Recognitions: Scholarship awarded by statistics faculty. Award from local ASA chapter for student excellence in statistics. Several awards from the math department. I passed the P Exam for actuaries.
Pertinent Activities or Jobs: Tutor, TA, and RA in undergrad. Working as Data Analyst since December, but I think only FSU knows that since I submitted apps earlier.

Letters of Recommendation: Not well known professors, but imagine all were strong and spoke to research potential.

Math/Statistics Grades:  

Math: Calc I-III (A, C, B ), Linear Algebra (C), Proofs (A), Abstract Algebra (A), Putnam Problem Solving (A), Real Analysis I (A), Real Analysis II (A), Topology (A), Complex Analysis (B), Functional Analysis (B), Measure Theory (C), 

Probability/Stats: Probability and Stats (A), Probability Theory (A), Statistical Theory (A), Stochastic Processes (A), Statistical Methods(A), Linear Regression (A), Data Science (A), Machine Learning (A)

CS: Computer Science I-II (B, A), Data Visualization (A), R Programming (A), Computer Vision (A)

Any Miscellaneous Points that Might Help: Retook CS II and Calc III for better grades.

Applying to Where: All statistics except UMich

UT Austin - Statistics PhD / Rejected on 03/12
UFlorida - Statistics PhD / Rejected on 02/27
Ohio State - Statistics PhD / Rejected on 04/15
Wake Forest - Statistics MS / Admitted on 02/19 (~15.7k funding)(no fees?)
UMich - Biostatistics PhD /  Rejected (PhD) / Admitted (MS fast track) on 02/03  (no funding)
Iowa State - Statistics PhD / Admitted on 03/24 (~18k funding + insurance)(~ 1k fees)
Florida State - Statistics PhD / Admitted on 02/21 (~17k-19k funding)(~ 2k fees)
TAMU - Statistics PhD / Pending 
Rice - Statistics PhD / Pending 
Rutgers - Statistics PhD / Pending  

 

Thoughts: This was my 2nd application cycle. Last year I made the mistake of applying to three schools ranked in the top 20 and one UC. It was hard but very worthwile waiting. I was able to make a bit of money working as a data analyst, I boosted my GRE Q by a good amount without much work, GPA went up with graduation, and got time to think more about research interests. With the help of people on this form I came up with a better list of schools. While there is a seemingly arbitrary nature to admissions, there are some things to note.

1. GRE is way more important than I thought, a good score won't get you in, but the overwhelming majority of applicants have good scores so you need one too (165+ and growing). 
2. The low profile of my school made me a risky applicant, but did not eliminate me.
3. Some schools seem to have a "type" of student they accept. Of the schools I got into, most of the domestic students are comparable to myself on a qualitative level.
4. Don't give up if you don't get in anywhere. Keep at it!

Edited April 16, 2020 by shuggie

[statapp123]

Undergrad Institution: Top 10 University known for grade deflation
Major(s): Math and Statistics
Minor(s):
GPA: 3.87

Type of Student: (Domestic/International (Country?), Male/Female?, Minority?) 
Domestic white male

GRE General Test:
Q: 167 (90%)
V: 170 (99%)
W: 4.0 (57%)
GRE Subject Test in Mathematics:
M: 760 (71%)
 

Programs Applying: Stats Phd's

 

Research Experience: Did a math GRE over the summer at my undergrad. After graduating, interned in a bio lab working on virology modeling papers with a publication under review.
Awards/Honors/Recognitions: Nothing beyond grade-related stuff
Pertinent Activities or Jobs: Calculus TA, hired by my college as a statistics tutor, TA in high school math camp

Letters of Recommendation: Math professor at my undergrad, statistics "senior lecturer" at my undergrad, boss at the biology lab.

Math/Statistics Grades:  Real Analysis, Linear Algebra, Probability, Statistical Theory and Methods, Abstract Algebra, Optimization, Numerical Analysis, Biostatistical Methods, Stochastic Processes, Algorithms, Complex Analysis, Regression Analysis (Mostly all A's with a few A-'s)


Applying to Where: 
UC Berkeley / Rejected 
University of Washington / Rejected 
Columbia / Rejected 

Cornell / Rejected

UChicago / Waitlisted, then rejected

 

UCLA / No response = rejected

 

University of Wisconsin / Accepted

UIUC / Accepted

U Minnesota / Accepted

Ohio State U / Accepted with fellowship = extra $$/no TA duties for first year

 

University of Boston (Statistics PhD within their Math Department) / One of my letters of recommendation never got sent...RIP

 

All acceptances were with TA offers of around $20,000. I have no idea what I'll end up doing research in, but I love math/statistics and I'm excited to explore! Don't be discouraged and think that a PhD is not for you if you're in the same boat.

[the_green_sunshine]

Undergrad Institution: One of UC San Diego, UC Davis, UC Irvine
Major(s): Mathematics and Physics
Minor(s): None
GPA: 3.59/4.0

Type of Student: Domestic Asian Male

GRE General Test:
Q: 166 (89%)
V: 167 (98%) 
W: 5.0 (92%)
GRE Subject Test in Mathematics:
M: 760 (71%)---submitted only to Berkeley, Columbia, Stanford, Penn State, UCLA. 
TOEFL Score: None 
 

Programs Applying: Statistics PhD

 

Research Experience: Attemped project with prof, two summer REUs, and two gap years in a quant ecology lab---but I ended up only getting a rec letter from the first summer REU.
Awards/Honors/Recognitions: I got one of those awards where you don't have to do anything, because one of my profs liked me. Free $1000 bucks...
Pertinent Activities or Jobs: TA for 3 years for math department

Letters of Recommendation: 1 young statistical learning prof at my school I took classes from, 1 old prof who advised my honors thesis, and 1 young prof at the REU who is outside the field

Math/Statistics Grades:  All on quarter system:

 

Lower div math/stat: 2 B+, 1 B-. GPA 3.1

Upper div math/stat (not including grad): 1 A+, 8 A's, 5 A-. Eight math classes, six stats classes. GPA 3.89. 

Grad math/stat: 2 A, 5 A-. Four math, three stats. GPA 3.78

Lower div physics:  1 A, 3 B+, 1 C. GPA 3.18

Upper div physics: 1 A+, 4 A, 3 A-, 1 B+ 3 B. GPA 3.6

Any Miscellaneous Points that Might Help: 

 

* Apparently the learning prof was good friends with someone on CMU admissions

* Did an expository honors thesis related to research at Berkeley and CMU

* Both stats profs said that they would have wanted me as a doctoral student in letters

* Berkeley asked for a separate list of math grades + textbooks, so I was able to largely omit my worse physics grades from it

Applying to Where: 
Berkeley - Stats PhD / Admitted

CMU - Stats PhD / Admitted 
NC State - Stats PhD / Admitted 

Purdue - Stats PhD / Admitted 

Rice - Stats PhD / Admitted 

Columbia - Stats PhD / Rejected 

Duke - Stats PhD / Rejected 

UMN - Stats PhD / Rejected 

Stanford - Stats PhD / Rejected 

UC Davis - Stats PhD / Rejected 

UCLA - Stats PhD / Never heard back as of April 17 

Yale - Stats PhD / Rejected 

Penn State - Stats PhD / Waitlisted / Declined 

Reflection

 

I had a weird application cycle. My results were inconsistent, just like my grades, which I at times neglected the importance of. I wouldn't even do homework assignments sometimes because I'd lost motivation. Personally I think my grades hurt me a lot---I'm sure if I had done better in physics, my returns would have been at least a bit better. Those B's were in important classes, too, like quantum. 

 

As far as class choice in math, I tried to pick a variety of classes for breadth of knowledge, and I always tried to take the hardest classes. I also went out of my way to take the harder versions of sequences when offered (e.g. Analysis, Algebra) and full sequences whenever I had the stamina---I think this shows depth. For graduate classes, as well, I didn't take the fun classes---I took the classes PhD students take for their qualifiers. 

 

And yet it turned out inconsistent, due to my terrible study habits---also reflected in my test scores. As far as research, sure, I had research experience, but it didn't come to any publications. I was late in applying to REUs, as well---though I did manage to pull off doing two of them (one after graduation in fact).

 

Ultimately, I think I was one of those cases where my recommendation letters were the most important part of my application, particularly my two stats letters. Something made them really like me. I think they appreciated my curiosity---I always asked a lot of questions, more than most other people, and tried to get to know them as people, as well, which I was able to do in the de-populated office hours of graduate classes. I also applied for the NSF, which they really appreciated seeing the research proposal for---I think it improved their letters. 

 

(I also, in one case, baked a cake for the class for the final exam. That was actually because I had a crush on a girl who was in the class, but it inadvertently made the prof remember me. I guess it helps to show that you're a person, too. But---perhaps this isn't something to be optimized for. I certainly didn't try to make them like me, or brownnose. And yet I was always surprised by how much they ended up believing in me. I feel like it has to do as much with my personality and soft skills---e.g. I'm curious about people, I love teaching---as it has to do with my academic merit.) 

 

Advice

 

* Grades matter in the "hard" classes. Attempt as you will---don't screw up too much, and recognize when you're burning out and need a breather. Take care of yourself. 

* I think GRE scores matter too. A lot. No matter what they say. 

* Take the "hard" grad classes if you can. Not just because the grades look good, but also it helps to connect with profs and get into research if your school has too many students. 

* If your recommenders really believe in you, don't be afraid to apply for the best schools. 

* Don't forget to be a real person outside of mathematics. I think I was in danger of that, but to the extent I didn't, I think it helped my case (if the recommenders knew, of course). 

* Before the REUs, I would actually try to do research with faculty, but it would always fizzle because I felt lost without the structure. If this is you, welcome it. That's how research is. You have to find the structure and focus yourself to try to put in a little time every week. It took an unnecessarily long time for me to learn this. 

* If you feel terrible after graduating, take a gap year.  

* Read your textbooks closely. 

 

 

 

 

Edited April 17, 2020 by the_green_sunshine

[the_green_sunshine]

Oh, forgot to say one thing. Notice that despite my lower grades in lower division courses, I still made it to upper-tier schools. I did not discuss or explain away this part of the application. Hope this helps someone. 

[AM61]

Undergrad Institution: Large Public State Flagship
Major(s): Mathematics (conc. in Math Stat)
Minor(s): Applied Stats, Political Science History
GPA: 4.0

Type of Student: Female Domestic (LGBT but no potential diversity points for that, since I did not mention it on applications)

GRE General Test:
Q: 168 (93%)
V: 170 (99%)
W: 5.0 (92%)
GRE Subject Test in Mathematics:
M: NA
TOEFL Score: NA
Grad Institution: NA
 

Programs Applying: Statistics (Ph.D. and Masters)

 

Research Experience: Worked with SAS in a biology lab as a freshman. Involved in a computational topology project with a group of graduate students in my math department during my senior year. No real stats research.
Awards/Honors/Recognitions: Phi Beta Kappa (inducted as a sophomore), Phi Kappa Phi, college and department awards, 7 semesters in a row on Dean's list, National Merit, Female State AP Scholar (that's a HS award but I listed it on my apps anyway)
Pertinent Activities or Jobs: Math tutor since high school, volunteered to lead a chapter of Mu Alpha Theta at local high school, math club officer

Letters of Recommendation: Very good recs (I imagine) from professors (2 math, 1 stats) who had a lot of confidence in me and said I was one of their best students.

Math/Statistics Grades:

Stats:

Intro Stats: A+

Statistical Analysis II: A+

Sampling Methods:  A

Statistical Theory: A+

R and Data Mining: A+

Math:

Calc III: A+

Linear Algebra: A

Probability: A+

Advanced Calculus (Real Analysis): A+

Mathematical Statistics: A+

Elementary Stoch: A+

Vector Spaces: A+

Comp Sci:

Intro to C++ Programming (IP)

SAS Programming (IP)
Any Miscellaneous Points that Might Help: Three of the stats classes listed above were graduate-level courses (though obviously open to undergrads) from my school's MSP program

 

I've heard that SOPs don't matter that much, but I think that mine was very professional and well-written and helped me quite a lot. One of the program coordinators I spoke with actually told me that they were impressed by what I had described in my SOP. I used it to highlight my topology research, since it wasn't featured anywhere else on my apps.

Applying to Where: 

PhD:

UNC - Stats Ph.D. / Admitted on 1/23/2020 with funding / Royster Fellowship offer on 3/6/2020

UT Austin - Stats Ph.D. / Admitted on 2/10/2020 with funding / Fellowship offer on 2/28/2020

Texas A&M - Stats Ph.D. / Admitted on 2/7/2020 with funding / Fellowship offer on 2/7/2020

Virginia Tech - Stats Ph.D. / Admitted on 2/12/2020 (ghosted about funding)

University of Florida - Stats Ph.D. / Admitted on 2/10/2020 (I declined before funding offer)

Carnegie Mellon - Stats Ph.D. (and Public Policy) / Rejected on 2/24/2020

MS:

Duke - MSS / Admitted on 2/18/2020 with partial funding

NCSU - MS / Admitted on 3/6/2020

 

Overall, I'm extremely pleased with where I got in and where I am attending (with great funding!). I went into the process hoping to get into 3 or 4 schools but got into every program except for my highest reach (CMU). I also was worried about getting stuck at a master's program with no funding and having to take out loans, but at the moment it looks like I'll be able to go through grad school debt free! Applying to several safeties and MS programs made me feel a lot better about the application process, even though I ended up being able to attend what probably turned out to be my top choice.

[bebop65]

 

 

Undergrad Institution: Large public university

Major(s): Applied Mathematics
GPA: 3.89(not including fall 2019 grades)

Type of Student: Domestic minority
GRE General Test:
Q: 166 (89%)
V: 165 (96%)
W: 4.0 (57%)

 

Programs Applying: Statistics PhD

Research Experience: Did a project related to dynamical systems with an applied math professor as a sophomore, and this last summer and fall did an independent study with a statistics professor. I didn’t make any real contribution to research in either of them which is what I thought was expected of me; now I think that to get a solid letter the most important thing is to show that you're willing to work hard and without anyone necessarily telling you to, even if you’re just learning the fundamentals of the topics like I was. I think it takes years of experience/mathematical maturity and a lot of time to invest into working on something to actually be productive, both of which undergraduates don’t generally have. I think professors understand that so if you can put in the time and learn things properly(don’t be in a rush) you’ll have a positive experience.

Letters of Recommendation: Two from the professors I did projects with, and one from the prof. whom I took analysis II, measure theory, and numerical analysis with. I did super well on many of the exams in those courses. In retrospect I think the letters were probably pretty strong and stronger than I thought they were when I applied.

Grades:

Mathematics:

Calc III: B(in high school, lol)

Linear Algebra and Differential Equations(proof based): A

Multi-Variable Calculus(proof based): A

Sequel to calc 3 for applied math students: A

Intro. to PDEs: B

Analysis I, II: A, A

Measure Theory and Integration: A-

Intro. to Probability Theory(proof based): B

Modern Algebra I, II: A, A

Numerical Linear Algebra: B+

Numerical Analysis: A

Intro. to Mathematical Optimization: A

Intro. to Stochastic Processes: A

 

 

Computer Science:

Intro. to programming: A

Combinatorics: A

Data structures: A

Physics:

I took 3 intro classes, a lab course, quantum mechanics, thermodynamics, classical mechanics, electrodynamics, and electronics and got all As. Initially I thought I wanted to do a physics PhD which is why I took so many physics courses and not so many statistics courses.

 

 

The 3 worst grades, in PDEs, prob theory, and numerical linear algebra were all in the spring semester of my sophomore year, which I think looks a lot better than having them spread out. I also got an A- from an independent study with a physics prof. in the summer after my freshman year(a bad time lol).

This last fall I took Stochastic Processes, Numerical Analysis and Electronics but maybe only one school saw the grades I got in them

Any Miscellaneous Points that Might Help:  None of my courses were strictly for graduate students, and I had no stats courses.

Applying to where:(all PhD):

All acceptances were with funding as a TA.

Illinois Urbana Champaign: Accepted

Penn State: Accepted

Iowa State: Accepted

Michigan: Accepted

Wisconsin: Accepted

Purdue: Accepted

U Washington: Accepted

CMU: Rejected

Duke: Waitlisted

UNC CH: Ghosted(rejected 4/21)

 

 

 

Reflection/Advice:

I’m very happy with my results but I think I was slightly too conservative in my school choices. If I could do everything over I would have replaced 2 of the lower ranked schools with reach schools, although all of the programs I applied to are great and I would have been happy to attend any of them. I don’t necessarily think it’s likely that I would have been admitted to Harvard or Columbia for example but in my case it would have been better to roll the dice than have 2 more acceptances. 7 acceptances is way too many to properly decide between and I ended up only really considering 3 of my acceptances as options.

I think that using this forum correctly is difficult because it’s really easy get into the comparison mindset where you pay particular attention to the applicants stronger than you, despite how few they may be, and despite the fact that the people here are at least a bit obsessive about getting into grad schools and therefore aren’t representative of the majority of people you’re competing with. It’s also really difficult for a stranger to look at your profile with all of the info you didn’t include and make an accurate judgement on your chances. My advice to future applicants is to primarily base where you apply on 1. where you’re excited about attending and 2. where applicants in previous years who have profiles similar to yours were accepted. Advice from others here on your chances could be viewed as a proxy for the actual results you can find on this site yourself.