trynagetby

Undergrad Institution: Ivy League
Major(s): Mathematics-Statistics
Minor(s):
GPA: 3.8999
Type of Student: Domestic Asian

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

TOEFL Score: NA
Grad Institution: NA
Concentration:  NA
GPA: NA
Programs Applying: PhD: Statistics, Biostatistics, ML
Research Experience: Freshman research in social work examining social media data,  publication with  name far back, Sophomore Biostatistics REU: First author paper at PSB, 2 year of research in statistical Neuroscience at home Institutio, publication with name far back.
Awards/Honors/Recognitions:  Nothing really
Pertinent Activities or Jobs:  Tutor/TA
Letters of Recommendation: 1 from Assistant Professor in Linear Algebra Class I did well in, probably not well known in stats (just a did well in class rec probably, but I was pretty interested in his research and we talked a bit). 1 recommendation from Sophomore REU prof. Probably extremely good, but he's a prof at a pretty unknown school. 1 recommendation from statistical neuroscience prof. He's extremely well known but I didn't do too hot in his lab so probably rec was just "this kid is persistent and can grind".
Math/Statistics Grades:
Bunch of lower division classes (A).
Real Analysis I/II - A
Abstract Algebra I  - B+
Fourier Analysis - B
Measure Theoretic Probability - A-
Numerical Analysis - A+
Analysis of Algorithms - A
Artificial Intelligence - A
Statistical Machine Learning - A-
Bayesian Statistics - A
Statistical Inference -A
Causal Inference (CS) - P (covid)
Abstract Linear Algebra - P (covid)

Applying to Where: (Color use here is welcome)
Stats:
School - University of Michigan
School - University of Washington
School - Duke
School - CMU
School - University of Washington
School - Wisconin-Madison
School - University of Texas Austin (waitlisted- then accepted)
School - UCLA (ghosted probably rejected)
School - UNC (ghosted probably rejected)
School - Cornell (ghosted probably rejected)
School - Rice
Biostats:
School - University of Washington
School - Harvard
Misc:
School - MIT (SES)
School - Georgia Tech ISYE (ML Program)
School - Northwestern IEMS
Advice for Posterity and Reflection:
Overall I'm pretty happy with my results and I'm pretty excited to be attending Duke. One caveat is that I severely underestimated my application (thought I would get into maybe one of UWashington, Duke, Mich). I didn't think I had a chance at Harvard/Berkeley  because of my so-so performancein upper division math classes and lack of graduate coursework , I didn't apply. My rec writers put a cap on schools beforehand (totally reasnoble given my paranoia) so I overspent my school allowance on safety schools. So future applicants please take risks because the regret is real. Tbh I probably wouldn't have gotten in to Harvard/Berkely but now I'll never know.
Some general advice
- all 3 of your letters don't have to be crazy strong. I think I only had 1 really strong letter that sang about my potential as a top researcher. While he was from a pretty unknown school he had sent quite a lot of students to top programs so that might have helped. The other letter from the neuroscience prof I did research for probably wasnt that great as I wasn't stellar and probably one of his worse students (but he has pretty good students). this letter probably said I was competent, hardworking and easy to work with. My last letter likely just spoke to my interest in math and that I was mathematically competent. So not crazy strong letters.
- undergrad school prestige matters a lot. So if you're from a top grade deflated school and have bad grades still shoot for the top! Hopefully my ehh profile encourages ya'll.
- Harvard/UWashington Biostatistics are not safety schools (typing this sentence, it seems obvious). I thought Biostatistics programs are much less competetive than statistics. But obviously that's not really the case as I got rejected by UWashington biostat and into UWashington Stat. Also I went to Harvard Interview day and people were super accomplished even before getting cut. I'd put those tier of biostat programs on the same competitiveness as UMich-Duke-UWashington Stats (probably difference that they place more emphasis on undergrad research and a little less on math).
- That being said if you're interested in Stat seriously consider top Biostat programs they do super cool work and I feel like I would have been very happy at Harvard if I didn't certain offers I did.
- Don't take math classes you're not interested in just to have more math classes. That's how my B in fourier analysis happened.
- Operations research programs are much less competetive (outside like MIT/Berkely) if you're interested in applied stats stuff.
- Hot take: I disagree with the prevailing wisdom that the SOP doesn't matter. I think Recs + Grades are much more important but with so many people applying I think that demonstrating that you can coherently express your research experience and that you know what type of work academic statisticians do via your research interests can move your application from the "consideration pile" to the "accept" pile.

Undergrad Institution: Ivy League
Major(s): Mathematics-Statistics
Minor(s):
GPA: 3.8999
Type of Student: Domestic Asian

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

TOEFL Score: NA
Grad Institution: NA
Concentration:  NA
GPA: NA
Programs Applying: PhD: Statistics, Biostatistics, ML
Research Experience: Freshman research in social work examining social media data,  publication with  name far back, Sophomore Biostatistics REU: First author paper at PSB, 2 year of research in statistical Neuroscience at home Institutio, publication with name far back.
Awards/Honors/Recognitions:  Nothing really
Pertinent Activities or Jobs:  Tutor/TA
Letters of Recommendation: 1 from Assistant Professor in Linear Algebra Class I did well in, probably not well known in stats (just a did well in class rec probably, but I was pretty interested in his research and we talked a bit). 1 recommendation from Sophomore REU prof. Probably extremely good, but he's a prof at a pretty unknown school. 1 recommendation from statistical neuroscience prof. He's extremely well known but I didn't do too hot in his lab so probably rec was just "this kid is persistent and can grind".
Math/Statistics Grades:
Bunch of lower division classes (A).
Real Analysis I/II - A
Abstract Algebra I  - B+
Fourier Analysis - B
Measure Theoretic Probability - A-
Numerical Analysis - A+
Analysis of Algorithms - A
Artificial Intelligence - A
Statistical Machine Learning - A-
Bayesian Statistics - A
Statistical Inference -A
Causal Inference (CS) - P (covid)
Abstract Linear Algebra - P (covid)

Applying to Where: (Color use here is welcome)
Stats:
School - University of Michigan
School - University of Washington
School - Duke
School - CMU
School - University of Washington
School - Wisconin-Madison
School - University of Texas Austin (waitlisted- then accepted)
School - UCLA (ghosted probably rejected)
School - UNC (ghosted probably rejected)
School - Cornell (ghosted probably rejected)
School - Rice
Biostats:
School - University of Washington
School - Harvard
Misc:
School - MIT (SES)
School - Georgia Tech ISYE (ML Program)
School - Northwestern IEMS
Advice for Posterity and Reflection:
Overall I'm pretty happy with my results and I'm pretty excited to be attending Duke. One caveat is that I severely underestimated my application (thought I would get into maybe one of UWashington, Duke, Mich). I didn't think I had a chance at Harvard/Berkeley  because of my so-so performancein upper division math classes and lack of graduate coursework , I didn't apply. My rec writers put a cap on schools beforehand (totally reasnoble given my paranoia) so I overspent my school allowance on safety schools. So future applicants please take risks because the regret is real. Tbh I probably wouldn't have gotten in to Harvard/Berkely but now I'll never know.
Some general advice
- all 3 of your letters don't have to be crazy strong. I think I only had 1 really strong letter that sang about my potential as a top researcher. While he was from a pretty unknown school he had sent quite a lot of students to top programs so that might have helped. The other letter from the neuroscience prof I did research for probably wasnt that great as I wasn't stellar and probably one of his worse students (but he has pretty good students). this letter probably said I was competent, hardworking and easy to work with. My last letter likely just spoke to my interest in math and that I was mathematically competent. So not crazy strong letters.
- undergrad school prestige matters a lot. So if you're from a top grade deflated school and have bad grades still shoot for the top! Hopefully my ehh profile encourages ya'll.
- Harvard/UWashington Biostatistics are not safety schools (typing this sentence, it seems obvious). I thought Biostatistics programs are much less competetive than statistics. But obviously that's not really the case as I got rejected by UWashington biostat and into UWashington Stat. Also I went to Harvard Interview day and people were super accomplished even before getting cut. I'd put those tier of biostat programs on the same competitiveness as UMich-Duke-UWashington Stats (probably difference that they place more emphasis on undergrad research and a little less on math).
- That being said if you're interested in Stat seriously consider top Biostat programs they do super cool work and I feel like I would have been very happy at Harvard if I didn't certain offers I did.
- Don't take math classes you're not interested in just to have more math classes. That's how my B in fourier analysis happened.
- Operations research programs are much less competetive (outside like MIT/Berkely) if you're interested in applied stats stuff.
- Hot take: I disagree with the prevailing wisdom that the SOP doesn't matter. I think Recs + Grades are much more important but with so many people applying I think that demonstrating that you can coherently express your research experience and that you know what type of work academic statisticians do via your research interests can move your application from the "consideration pile" to the "accept" pile.

Undergrad Institution: Ivy League
Major(s): Mathematics-Statistics
Minor(s):
GPA: 3.8999
Type of Student: Domestic Asian

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

TOEFL Score: NA
Grad Institution: NA
Concentration:  NA
GPA: NA
Programs Applying: PhD: Statistics, Biostatistics, ML
Research Experience: Freshman research in social work examining social media data,  publication with  name far back, Sophomore Biostatistics REU: First author paper at PSB, 2 year of research in statistical Neuroscience at home Institutio, publication with name far back.
Awards/Honors/Recognitions:  Nothing really
Pertinent Activities or Jobs:  Tutor/TA
Letters of Recommendation: 1 from Assistant Professor in Linear Algebra Class I did well in, probably not well known in stats (just a did well in class rec probably, but I was pretty interested in his research and we talked a bit). 1 recommendation from Sophomore REU prof. Probably extremely good, but he's a prof at a pretty unknown school. 1 recommendation from statistical neuroscience prof. He's extremely well known but I didn't do too hot in his lab so probably rec was just "this kid is persistent and can grind".
Math/Statistics Grades:
Bunch of lower division classes (A).
Real Analysis I/II - A
Abstract Algebra I  - B+
Fourier Analysis - B
Measure Theoretic Probability - A-
Numerical Analysis - A+
Analysis of Algorithms - A
Artificial Intelligence - A
Statistical Machine Learning - A-
Bayesian Statistics - A
Statistical Inference -A
Causal Inference (CS) - P (covid)
Abstract Linear Algebra - P (covid)

Applying to Where: (Color use here is welcome)
Stats:
School - University of Michigan
School - University of Washington
School - Duke
School - CMU
School - University of Washington
School - Wisconin-Madison
School - University of Texas Austin (waitlisted- then accepted)
School - UCLA (ghosted probably rejected)
School - UNC (ghosted probably rejected)
School - Cornell (ghosted probably rejected)
School - Rice
Biostats:
School - University of Washington
School - Harvard
Misc:
School - MIT (SES)
School - Georgia Tech ISYE (ML Program)
School - Northwestern IEMS
Advice for Posterity and Reflection:
Overall I'm pretty happy with my results and I'm pretty excited to be attending Duke. One caveat is that I severely underestimated my application (thought I would get into maybe one of UWashington, Duke, Mich). I didn't think I had a chance at Harvard/Berkeley  because of my so-so performancein upper division math classes and lack of graduate coursework , I didn't apply. My rec writers put a cap on schools beforehand (totally reasnoble given my paranoia) so I overspent my school allowance on safety schools. So future applicants please take risks because the regret is real. Tbh I probably wouldn't have gotten in to Harvard/Berkely but now I'll never know.
Some general advice
- all 3 of your letters don't have to be crazy strong. I think I only had 1 really strong letter that sang about my potential as a top researcher. While he was from a pretty unknown school he had sent quite a lot of students to top programs so that might have helped. The other letter from the neuroscience prof I did research for probably wasnt that great as I wasn't stellar and probably one of his worse students (but he has pretty good students). this letter probably said I was competent, hardworking and easy to work with. My last letter likely just spoke to my interest in math and that I was mathematically competent. So not crazy strong letters.
- undergrad school prestige matters a lot. So if you're from a top grade deflated school and have bad grades still shoot for the top! Hopefully my ehh profile encourages ya'll.
- Harvard/UWashington Biostatistics are not safety schools (typing this sentence, it seems obvious). I thought Biostatistics programs are much less competetive than statistics. But obviously that's not really the case as I got rejected by UWashington biostat and into UWashington Stat. Also I went to Harvard Interview day and people were super accomplished even before getting cut. I'd put those tier of biostat programs on the same competitiveness as UMich-Duke-UWashington Stats (probably difference that they place more emphasis on undergrad research and a little less on math).
- That being said if you're interested in Stat seriously consider top Biostat programs they do super cool work and I feel like I would have been very happy at Harvard if I didn't certain offers I did.
- Don't take math classes you're not interested in just to have more math classes. That's how my B in fourier analysis happened.
- Operations research programs are much less competetive (outside like MIT/Berkely) if you're interested in applied stats stuff.
- Hot take: I disagree with the prevailing wisdom that the SOP doesn't matter. I think Recs + Grades are much more important but with so many people applying I think that demonstrating that you can coherently express your research experience and that you know what type of work academic statisticians do via your research interests can move your application from the "consideration pile" to the "accept" pile.

Word of warning, UT Austin is way more competitive than its rankings would indicate (probably as competitive as like TAMU/UNC/Winsconsin/NCSU).

Not even close, these programs are not in the same tier.  UW

Given your interest, I think Harvard is best fit. Imai has affiliation at Kennedy school, Neil Shephard is affiliated at economics. Murphy is also a big name here doing causal inference and reinforcement learning affiliated to CS department. There is no problem that you seek additional advisors at MIT or other Harvard departments. You can easily find someone at MIT to supplement for (3) (4). Everyone is saying Stanford stats but they are mainly about highly mathematical/theoretical high-dimensional stats and probability theory. So I guess you will need to go to their CS department to find advisors? Stanford probably is not that of a good fit for you. 

It's hard to go wrong with Stanford. Assuming you actually got in to Stanford... go to Stanford. 

I think you can check out my profile and results for a comparable example. I had a little more math and a lot more research than you, but also a lot of Bs, plus your school's reputation is slightly higher than mine. I also really only had 1 strong rec letter and a rec letter where I just asked a prof who taught a class I did well in.
I still got into the lower top tier range of Stat PhDs (UMich, UW, Duke,etc..) and I suspect that you would too (at least one of them if you applied to all). Cracking Harvard/Berkely/CMU will be hard but you should definitely apply.

In terms of classes, I'd take whatever interests you and you think you can do well in. Many schools won't even ask for fall grades.
Good Luck!

As someone who applied to both programs and got into some of both, I would pay more attention to the type of work that professors in Bio-statistics and statistics programs do and the coursework rather than the label. Biostatistics programs generally do more applied/methodology work that is focused on being immediately applicable to biomedical problems (hypothesis testing, Causal inference, etc...). Statistics programs generally do a wider range of stuff and if you want to do crazy theory like crazy asymptotic statistics or high-dimensional theory then you'll likely only be happy in a statistics department. Im still speaking in generalities because if you go to somewhere like Harvard you have people like Rajarshi Mukherje who are more theoretical than most people even in a pure Stats department like Duke.
Personally I think if you're truly interested in biological applications then biostats departments like Harvard/UWashington are the way to go as you get so much exposure to biomedical problems that its probably academic heaven. Otherwise it might be a little torturous as departments like Harvard, depending on the training grant you're on, will force you to take many classes in your field of specialization (e.g cancer, genetics, environmental health). Also it'll kinda suck if everyone around you is super passionate about genetics and you're still confused about what a chromosome is (I speak from my experience at a statistical genetic REU).
Unlike me, I think you're a strong enough applicant where you don't need to hedge your bets with biostatistics program unless you're really interested in biology stuff. So it really comes down to what you want.

As someone who applied to both programs and got into some of both, I would pay more attention to the type of work that professors in Bio-statistics and statistics programs do and the coursework rather than the label. Biostatistics programs generally do more applied/methodology work that is focused on being immediately applicable to biomedical problems (hypothesis testing, Causal inference, etc...). Statistics programs generally do a wider range of stuff and if you want to do crazy theory like crazy asymptotic statistics or high-dimensional theory then you'll likely only be happy in a statistics department. Im still speaking in generalities because if you go to somewhere like Harvard you have people like Rajarshi Mukherje who are more theoretical than most people even in a pure Stats department like Duke.
Personally I think if you're truly interested in biological applications then biostats departments like Harvard/UWashington are the way to go as you get so much exposure to biomedical problems that its probably academic heaven. Otherwise it might be a little torturous as departments like Harvard, depending on the training grant you're on, will force you to take many classes in your field of specialization (e.g cancer, genetics, environmental health). Also it'll kinda suck if everyone around you is super passionate about genetics and you're still confused about what a chromosome is (I speak from my experience at a statistical genetic REU).
Unlike me, I think you're a strong enough applicant where you don't need to hedge your bets with biostatistics program unless you're really interested in biology stuff. So it really comes down to what you want.

As someone who applied to both programs and got into some of both, I would pay more attention to the type of work that professors in Bio-statistics and statistics programs do and the coursework rather than the label. Biostatistics programs generally do more applied/methodology work that is focused on being immediately applicable to biomedical problems (hypothesis testing, Causal inference, etc...). Statistics programs generally do a wider range of stuff and if you want to do crazy theory like crazy asymptotic statistics or high-dimensional theory then you'll likely only be happy in a statistics department. Im still speaking in generalities because if you go to somewhere like Harvard you have people like Rajarshi Mukherje who are more theoretical than most people even in a pure Stats department like Duke.
Personally I think if you're truly interested in biological applications then biostats departments like Harvard/UWashington are the way to go as you get so much exposure to biomedical problems that its probably academic heaven. Otherwise it might be a little torturous as departments like Harvard, depending on the training grant you're on, will force you to take many classes in your field of specialization (e.g cancer, genetics, environmental health). Also it'll kinda suck if everyone around you is super passionate about genetics and you're still confused about what a chromosome is (I speak from my experience at a statistical genetic REU).
Unlike me, I think you're a strong enough applicant where you don't need to hedge your bets with biostatistics program unless you're really interested in biology stuff. So it really comes down to what you want.

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

@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)".
 

Sounds like Stanford's a real possibility dude, so I'd just apply to all the top places. Because you're domestic I really wouldn't bother applying lower than Michigan/UWashington/Duke. Actually should probably apply to like 2 lower schools in the top 20 out of an over-abundance of caution.

 

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!

Very interesting story. Maybe he is not dead-set on getting a PhD? Yale stats is actually very good. With guys like Harrison Zhou, Zhou Fan and Van Vu, I can even see one choosing Yale over Stanford when admitted to both. Not to mention the tremendous cost of money and time and the uncertainty of actually getting into Stanford (or even Yale itself) 2 years later. Sounds like a terrible decision. 

Sorry, was talking about Stats. The starter of the thread I think is applying to Stats programs. Funny how you get to know posters on the thread haha.

Greetings everyone!  I'll defer any commentary about Duke's coursework to another recent post of mine, but I wanted to clarify a couple things:
1. I think(?) Duke got referred as having 2 qualifying exams, but we only have 1!  We have the actual, appropriately named Qualifying Exam (formerly the First Year Exam -- it's still administered after the first year), and then a later Preliminary Exam, which I'm guessing is what's getting confused for a second qual.  I'm not entirely sure how to characterize the Prelim Exam myself (the description of it is here), but I'd probably call it closer to a thesis proposal than a qualifying exam in the usual sense, at least functionally.  
2. (Sigh...) I've lived in Morningside Heights before, I've lived in Durham before.  Anecdotally, I've been fine both places (and I assume I would've been in Boston as well).  Regardless of that, I'm really not convinced that debating the safety of large, highly-populous neighborhoods or entire cities without some rigorous framework is a productive conversation, y'all.  
 

The answer would be Stanford for me by a very long mile. The program is very elite, much more so than Berkeley's program in my opinion. The fact that you are from the Stanford program would be already impressive on your PhD application--not so much for Berkeley MA. The reason? Firstly, Berkeley MA admission is much less competitive. Simply getting into Stanford MS indicates you are elite undergrad, a class above anyone else from a master program. The distinction to me is very clear.
Second, Berkeley's master course is watered down from their regular PhD version. Sure, you can substitute for PhD equivalents on your own initiative but if you apply elsewhere people may just assume that you have less rigorous coursework.
To put it plainly, my first impression would be Stanford MS students are of a higher calibre. 
You do not need to worry about no "formal thesis" at Stanford. The thesis formality is simply putting together a document that, at master level at least, no one will care. It could be of very high calibre or just some reading notes, but the thesis itself as a document does not matter either way. The only way your master research factors into phd admission is (i) having a strong recommendation from renown profs who specifically comment on the quality of your work (ii) publish it at top venue of your field before phd application is due.  Both (i) and (ii) have nothing to do with whether you have a formal thesis or not. Actually it is better to not to have it because the only difference is you spending like two weeks to type it up from work already done. 

Hard to say now. Harvard's courses have become harder this year. The 2nd inference class now follows Van der Vaart almost exactly--we used to just cover MLE consistency/normality and some less theoretical Bayesian stuff like model comparison, mcmc. 2nd prob instalment also paces faster than previous iterations. Looks like Duke could indeed be the least demanding in terms of course work. 

I can't comment on the quality of the programs, but I went to Columbia undegrad so I can comment on location and housing. People have different feelings about the location because while Columbia is in Manhattan, it doesn't really have the Manhattan feel. It's definitely more residential and family orientated (which I like). If you live around the campus you have really easy access to the 1/2 subway line which gives super good access to downtown Manhattan and Brooklyn. If you're Asian, there's an H-Mart super close so you can get Asian groceries and Westside market is great. Central and Riverside park are nearby which is also very nice if you like jogging.
Disadvantages are that its really not the Manhattan experience (I lived in East Village one summer, and its a completely different feel). Restaurant/Bar scene are meh (but you'll likely be broke anyway). The Affordable student housing that the previous poster mentioned is affordable, but still kinda sucks as you will likely have a roomate (roommate in the sense of sharing a room, like as a freshman in undergraduate). Many students decide to rent a place in Brooklyn but then you have to commute an hour to school. Morningside rent is pretty pricey.
Winters are kinda sad (probably better than Boston lol). But Springs/Summers are super nice. I don't really have any advice, just wanted to give some honest location info.

Sorry, was talking about Stats. The starter of the thread I think is applying to Stats programs. Funny how you get to know posters on the thread haha.

Judging from the email they replied all to a while back, it seems like they put everyone not accepted on the waitlist and rejected no one lol.

You are on good hands at Duke, best of luck. 

You really couldn't have made a wrong choice. Duke is a great place (maybe the best place) for Bayesian statistics (e.g., Herring, Dunson). Your stipend will certainly go further in Durham than Seattle. Best of luck!