Nothalfgood

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.

Undergrad Institution: Small state school (>200 USNews)
Major(s): Data Science
Minor(s): Mathematics, Economics
GPA: 4.0
Type of Student: Domestic white male
 
GRE General Test:
Q: 166 (87%)
V: 169 (99%)
W: 5.0 (92%)
 
Programs Applying: Statistics, Biostatistics
 
Research Experience: 
Research assistant in public policy 2019-2020 [3 non-peer reviewed client papers published, 1 small undergraduate research grant] Several miscellaneous research projects in coursework Two summer REUs (2020 & 2021) in applied math & statistics [1 poster presentation] Research assistant in data science & computational statistics 2020-present [3 first-author peer-reviewed journal/conference publications, 1 non-first-author peer-reviewed journal publication, 1 conference speed talk] Awards/Honors/Recognitions: 
Honors college member at my university Full tuition undergraduate scholarship Won “Best Visualization” at local DataFest competition Pertinent Activities or Jobs: 
Resident assistant at my university Teaching assistant for machine learning course Letters of Recommendation: Three strong letters from professors in mathematics and computer science who know me personally (including research advisor), all from my university
 
Math/Statistics Classes: Calculus III, Discrete Math, Linear Algebra, Advanced Linear Algebra, Real Analysis I & II, Numerical Analysis, Numerical Optimization [grad level], Math Modeling, Elementary Statistics, Probability, Mathematical Statistics [grad level] (all As)
 
CS/DS Classes: Intro to Data Science, Data Analysis & Visualization, Objected-Oriented Programming, Software Design, Algorithms & Data Structures, Database Design, Computer Graphics, Machine Learning, Wireless Communications [grad level], High-Performance Scientific Computing [grad level] (all As)
 
Any Miscellaneous Points that Might Help: President of data science organization at my university, lots of service to my department (speaking at Open Houses, etc.)
 
Applying to Where:
Harvard - Biostatistics - Interview / Accepted / Attending!
Carnegie Mellon - Statistics & Public Policy - Rejected
Yale - Statistics & Data Science - Rejected
U of Michigan - Statistics - Ghosted
UCLA - Statistics - Interview / Ghosted
Penn State - Statistics - Accepted
Colorado State - Statistics - Accepted
 
Comments: 
GradCafe users advised me to apply to Biostatistics PhD programs, stating that given my background and interests in applied stats, they would be a much better fit. At first, I was highly skeptical, and since I did not have the resources to apply to lots of programs, I decided on just one top biostat program (Harvard) in case their advice really was true. Based on my results and experiences during interviews, this turned out to be the best decision I ever made in my life. My advice: if you are a domestic student applying to stats PhDs, consider a few Biostatistics programs as well.
 
And thank you, frequent users of this forum - I am incredibly grateful for the wonderful advice posted here!
 

Final Update-
I got into UT Austin (Stats), Boston University (Biostats), Colorado School of Public Health (Biostats) and UT HSC Houston (Biostats). Since UT was my dream school, I accepted their offer recently. I am very happy with the outcome!
My profile may seem weak to Domestic or other international applicants but things that helped me were my nationality (Indian) and my recommenders. I got into UT because my one of my recommenders knew closely a prof at UT and she got me in touch with him. Also, UT was keen to have Indian students this year so that also worked into my favor. 

If you look at the number of applicants for schools that release data for previous years (Duke, Cornell for example) the number of applicants in the 2021-2022 admission cycle was very much within normal variation. So if the beginning of the pandemic didn't budge numbers too much, I don't think that this years numbers will depart from previous years very much either (aka there should not be a flood of applicants this year).
Anecdotally while there are people who delayed applications because of Covid, in my experience there are also people moved their application up a year for various reasons (I did as well as some other people I know). So it's kind of a wash.

Regarding the objections, I must reiterate that it depends on (i) math maturity (ii) how that class is taught at that particular year.
The difference could literally be 6 hour/week v.s. 60 hrs per week for the same class with different instructors. Same thing goes with one's math maturity. 
From what I know, if Zhou Zhou or Rosenthal still teaches grad probability at UofT, it might be very  doable. I heard that Zhou Zhou is drier/technical but Rosenthal on the other hand should stick to his book "A first look..." and has a reputation of being lenient and less technical. Take a read and see if that works for you.  There seems to be a separate offering at math department now by D. Panchenko. Never took a class from the man but his books are among the best expository materials, written in astounding lucidity. He himself is a brilliant researcher with deep work in spin glass and inequalities. I personally would cherish an opportunity to take class with a master like that. Don't be too obsessed with grades. 
No ideas on real analysis. 

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.

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!  

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.      

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.

I'm sure there are plenty of examples of people getting into some top math programs without having a math degree, and statistics is certainly one of the most natural alternatives if you've already pretty much mastered real analysis and linear algebra, so my opinion is that it's worth a try to apply. I think there are some applied math programs that blur a lot of the lines between pure math and statistics like at UMaryland and Johns Hopkins which you may be interested in too.
In some sense, you may be unable to totally "escape" applications at this point, but I think you could find stats or applied math programs where you could spend virtually all of your time working without any real data and instead on almost exclusively analysis and topology flavored problems. That is my impression from some current graduate students in statistics at schools like UMichigan and UWisconsin.

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.  

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.

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!

I just can't believe what just happened; I got an offer from OSU! THIS IS INSANE!!

For everyone who has received all (or most of) their admissions decisions already, feel free to add your profile to the 2021 Applicant Profiles and Admission Results page! I'm sure future applicants would appreciate it.

@DanielWarlock gave a pretty comprehensive answer and I'm not knowledgeable about theoretical stats at all. I'll just throw in an observation that at all 4 different Stats/Biostats visit days at top 10 programs I've been to,  someone has asked about how schools stack up in theoretical statistics and a professor said a variation on  "oh for theoretical statistics, you should definitely consider (insert other Uchicago prof), and Chao Gao that guy is (insert superlative)".
 

Both schools are focused around the theme of high-dimensional stats. But risking oversimplification, a quick summary of their difference is: CMU is more "CS"; UChicago is more "mathematical". If you consider yourself more of a mathematician/probabilist, go to Chicago. If you consider yourself a computer scientist who looks at more applied stuff, then go to CMU. I will now further explain what I mean. 
CMU focuses more heavily on more applied, interdisciplinary stuff like neurosciences, astrostatistics, social sciences and yes sports analytics.  Of course, most of these are done under the tag of "high-dimensional statistics".  But I would even go so far to say CMU stats has more of a "CS flavour" if you know what I mean. On a related note, CMU is also much stronger on causal inference, which is also more "CS". I also feel the organization is very similar to what I see at EECS at MIT: they have all these themed working groups like "astrostats group", "causal inference group". So the community based activities like colloquium/talks, reading groups will be more specifically tailored to your subfield. 
Chicago is more theoretical and will probably be more so in the coming years based on their new hires. Maybe "theoretical" is not a good descriptor. What I mean is that their new hires now mostly have tags such as "physics", "statistical mechanics", "random matrices", "Fourier/harmonic analysis", "combinatorics", "random graphs". Chicago is definitely more mathematical and has a taste of more probabilistic things. They even hired student of Borodin who does hard-core math. 

I agree with bayessays, but I did want to add in one edge case -- I really wanted to go to CMU in part because of their strong collection of people working on applications in sports (more the students than the professors I think, but they host a summer research program for sports statistics too).  Of course, that's a niche interest, so YMMV.

Besides the very personal city preferences (Hyde Park isn't the most desirable place to live, but you have access to a much bigger city than Pittsburgh), I agree that the theoretical nature/intensity of the programs would be my biggest factor.  If I was very confident in my math abilities (such that I wouldn't be worried about failing quals) and I wanted to do very theoretical/mathematical statistics, I would go to Chicago. Otherwise I would probably go to CMU.  Of course, these are broad generalizations and if there were specific professors I wanted to work with at one, that would be a different story.  Either way, both great choices, congrats!

I hope you all have been having a spectabulous Spring and are excited about your options for this Fall if you have been applying to schools this season.
I've been lucky to receive very good results for my PhD applications, and I do believe that I'm ready to make my decision. However, I would like to crowdsource my question just for that last drop of insight, and maybe also because I'm curious: which statistics PhD program between University of Chicago and Carnegie Mellon University would you be most inclined to choose (if those were both your best or only options)?
The typical points of comparison I've approached are along these lines: UChicago has a more comprehensive theoretical program with many courses and course options, offers somewhat safer summer funding to most students, and has collaborations with nearby institutions like Toyota Tech and Argonne; CMU has more freedom built into their program without qualifying exams or as strict and intense a course load, emphasizes interdisciplinary work and applied projects more, and is located in a safer and more affordable neighborhood.
I think that these may be enough to decide which department culture is more to one's general preferences, but it's not a total and unilateral comparison. I have met current students at both programs who faced the same decision, so I'm confident that there's no wrong answer. I can only truly learn about department culture by living and interacting in the respective environments. As such, I have come to a biased decision from these simple impressions alone and would like to see whether I'm approximately in agreement with the broader community of new grad students in my field.

People have unfortunately been accidentally cc'ing me on their emails to the UCLA coordinator. (UCLA has realized to remove me before replying)
If you're reading this thread and about to reply to the UCLA email thread to ask them for an update, MAKE SURE TO REMOVE THE GMAIL ADDRESS FROM THE CC LINE!

Hi @Nothalfgood, I'm also looking for some fun stuff to learn this summer! BTW I'm an incoming PhD student in statistics. Here's a page I found particularly helpful: https://github.com/sshkhr/awesome-mlss. If you want someone to form a study group or something, feel free to PM me.

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.

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.

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.