statfan

UNC's program is inarguable better. They are not even close.

Michigan for sure.  Outside of the fact that it is universally considered a stronger department, Michigan's generous stipend in Ann Arbor will give you a lot better quality of life than at UCLA.

I think overall Toronto is a step above NCSU. As you can see from the faculty list of the statistics department at Toronto, most of them obtained their PhD from top schools in the world and consistently publish at top statistical journals. They even have 2 COPSS award winners. In particular, if you want to specialize in probability, Jeffery Rosenthal is a perfect choice. While NCSU has a good statistics department with a wide range of research areas, the department is generally perceived as more applied with close ties to industry. The academic placements at Toronto are better than those of NCSU.

Your overall gpa is low but you did well in most math courses, and your ability to do math is what admissions committee mainly cares about. If your bombed electives courses that are not relevant, I don't think it's a big deal. If I were you, I would take more advanced proof-based courses such as grad level real analysis and possibly take the math subject GRE to strengthen my profile. If you do well in them, you should have a decent shot at schools between Penn State and Florida and I think it is not impossible to get into a couple of top 20 programs. However, competition is very stiff in recent years and you should add a few safeties outside of top 50.

You have more than sufficient math background to apply for statistics PhD. It's always good to know more math, and this will help for any quantitative disciplines. Much of the statistics theory is related to real analysis/measure theory, but this doesn't mean that algebra is not or will not be useful. Indeed, algebra is starting to gain its popularity in statistics and there is an emerging area called algebraic statistics. That being said, if you are interested in these courses and have the time, you can take both. However, these are not required for admission to statistics PhD.

I found Daniel's response misleading. A 3.5 GPA from an Ivy is not stellar but good enough for master's admission. Master's programs usually have much higher admission rate than PhD programs and as long as you meet the minimum requirement you will be considered. Coming from an Ivy with decent a GPA helps a lot and I can see you get into top 10 master's programs for statistics.
 

I found Daniel's response misleading. A 3.5 GPA from an Ivy is not stellar but good enough for master's admission. Master's programs usually have much higher admission rate than PhD programs and as long as you meet the minimum requirement you will be considered. Coming from an Ivy with decent a GPA helps a lot and I can see you get into top 10 master's programs for statistics.
 

You have an excellent math background. However, if your school does not have track records of sending students to top phd programs, it would still be difficult for you to get in. If that is the case, you should apply very broadly. Your chances depend a lot on the quality of your references and if your referees are well known, that will help you a lot and you may get into a couple of the top 20's. You should definitely apply to the school where you did REU at. 

You could boost your GRE scores, but it won't be a big issue. And make sure you get "strong" letters from famous professors. What I learned from this year is that funding situtation of the programs, your ethnicity background(international male always gets the most fiercer competition), your undergraduate/master institution(especially if there are many applicants from your institute, they would only admit two at most, no matter how strong you are), admission committee's research interest that year, and all sorts of idiosyncratic stuffs come in role. Another reason for applying so-called safety schools is that, if you check the number of admitted PhD students of past 5 years of any school, you will see that the openings have slightly dwindled recently, this may due to the Donald Trump's administration. In addition, many programs you listed actually do prefer their own master's student. This is what I have heard from several guys doing PhD in the programs you listed. 

As someone who had a similar background with you(while you have more courseworks), I cannot help emphasizing enough to apply for more safety schools. All the schools on your list are very difficult to get in and most of them have openings less than 10 spots out of 300 applicants. I strongly recommend applying for NCSU, ISU, PSU and some good UC schools. No offense but, these schools are by no means easy to get in even with your background nowadays, but definitely more in between safety and reach, given the fact that competition between international students are getting fiercer these days.

I think you have good chances at some of the schools but I think you should definitely try to improve your GRE W and V scores for a better shot

I'd echo what others have said; you might have a shot at a top school, but I wouldn't bank on getting into one of Stanford/Berkeley/Chicago/Penn or UW/Hopkins. I think your chances are better at Wisconsin, Michigan, and Columbia, but I would classify those more as reasonable targets than safeties. If I were you, I'd probably be mostly targeting programs ranked between ~10 and 30 in the combined stat/biostat US News rankings.

You have a fantastic math background (as well was quant GRE) from a good school. As for your research background, it is hard to gauge without any publications (though the fact that you have publications on the way means that you can link your working paper with the application for review). To make up for this, I would try to assess the likelihood of strong LOR's from your research supervisors/teachers. Do you personally think they will be strong?

Overall, your background is extremely solid but your Statistics list is very top-heavy, making it likely you may not get in anywhere. You seem like a strong bet for 10-20 ranked programs so I would apply to a couple more in that range just to be safe. I'm not super sure about Biostatistics so I won't comment on that.

...And I am interested to learn how to deal with bad grades as well. I am an engineering major and have poor grades (worse than yours) in some of those courses, but like you have a strong math background (3.97 math GPA, but no stats classes).

I second that you have a chance at a top tier program but you might want to add some safer options.  You could alternate your third rec letter depending on the program, but I don't think it matters much either way.   I doubt the couple of Bs/Cs would stand out given your other grades, and I wouldn't bring attention to them in your SOP.  Your GRE verbal and writing scores are low but I think their function in stats programs is to gauge your general english abilities since you aren't going to write a lot of 30-minute essays or take vocabulary tests in graduate school.  If english is your native language, I don't think those scores really matter that much.  If you think you could easily increase your scores then its maybe worth retaking. 

GRE is a filter and unless you bomb it, it won't matter much. Your official transcript should not show your GPAs since different universities have different rules of calculating GPAs. The admission committees will mainly focus on grades in individual courses that are relevant and you did well in all of them. That being said, you are competitive for any masters program so maybe remove some lower ranked schools like Ohio state and Colorado, and I feel that with this profile you are even competitive for top 20 phd progams.

What ended up happening here? Did you end up getting into a Ph.D. program that you wanted, or went the masters route? Thanks!

Hey, 
Not sure if this is the right place for this, but can anyone chance me / give general advice for the fall 2019 application cycle? I'm interested in applying for PhD programs. 
Stats:
Undergrad institution: Top 3 US News
Major: Statistics and Math
Overall GPA: 3.87/4.00
Quantitative GPA: 3.95/4.00 (three A-s, the rest were As) 
GRE: 170/170/ 5
Math GRE: Should I take this over the summer?
Research:
I really haven't done much statistics research up until now, but am currently working on a senior thesis (I am a junior) with a famous professor in causal inference. I'm counting on this turning out well. 
1 REU at lawrence berkeley lab doing physics research
Summers:
- 1 internship doing software engineering / data science
- REU at lawrence berkeley
- Committed to internship at top tier tech company for summer '18. Will simultaneously work on my thesis. 
Coursework: 
- 4 grad level stat/ CS courses (A, A- ,A- , the fourth one is this semester)
- All As in undergrad level stat, math, and CS classes (complex analysis, algebra, most of the undergrad stat courses that are offered)
Other relevant info:
- school teaching award for my work as a TA in 3 semesters
- award for being in the top 10% of the class
 
 
 
 
 
 

This seems to be the thinking from many people, and while it may be true in some programs, it's not true in the others. For example, I attend a top-5 biostats program (not UW), and our coursework covers measure theory, limit theory, decision theory, etc. just like a traditional statistics program would.
I don't think you can put all biostatistics programs in a vacuum and simply say "well it's biostatistics so it's less theoretical." The same goes for statistics--some even top tier programs (e.g., NCSU), will be more applied than the more theoretical biostatistics programs. We're not talking about statistics vs biostatistics here, we're talking about UW Biostatistics vs. CMU Statistics. 
 

I am applying for fall 2018 admissions so I am not an expert, but I have read the past admissions profiles and survey results so many times I almost have them memorized.  
Your list is a little top heavy, but you have great grades from a good institution.  You won't get in everywhere with that list, but maybe 2-4 places on the list assuming a good GRE.  Try to get some more research experience (if possible), and study for the GRE.   Take a general GRE practice test as soon as you can.  Ideally, you would have 167+ on quant and 160 on verbal, and 80%+ percentile on the math subject test.  I would consider signing up for the April 2018 math GRE and take the general by August or September.  I recently wrote a post with general GRE advice here.  I was worried about the process too and adding safer (no school is a safety school though) programs on my list made me personally feel better.   You can read last years profiles here and you can find more by searching.  Also be prepared to spend $1000-1500 on application fees (Columbia's was $110), GREs, and sending transcripts/score reports.  Texas A&M had a free application this year that required no official score reports or transcripts and if they do that again so should consider adding them to your list.  

I am a statistics PhD program applicant for fall 2018, so I am not an expert.  I have however read most of the applicant profiles threads, and old posts about admission chances.  
Baylor doesn't really have a masters program.  I am not sure if it will let you apply.  Baylor is my first choice and I have visited.  They say they only have PhD students and the master's program exists in case people want to leave with a masters degree after two years.   You might have a shot at Baylor's PhD program,  but your real analysis grades will likely hurt you.   Your GRE much higher than the average 164Q/155V they told me.  Baylor's program is biostats focused but they have people doing other things.  You mentioned in your other thread that your endgoal is a PhD, so I am not sure if you want to go straight into a PhD program.
I think you would have a shot at getting into most public non-elite masters' programs,  but I don't know if anyone would fund you or if you need funding.   Some domestic students have gotten funding at Florida State and Iowa State in the past for their masters' program, but I don't think they fund all of their domestics.   Duke and Columbia are very competitive and I think your math background could not be strong enough.   Columbia has a MS in quantitative methods for social science which I imagine wouldn't care about your math background, but I don't know if that would help you get into a Statistics PhD program.   It also depends on what your undergraduate institution was.  If it is UChicago or someplace that is commonly known for grade deflation, that may help cancel out the grade because a B/C+ there might be As and B+s at some places.
Really it depends on whether or not you need funding, and what you want to do after you graduate.  If your end goal is a PhD in stats I would get an MS in statistics that requires/allows you to take theory over an  MS in math.  I know nothing about applying to math programs but I think it would be easier to get into a stats program over a math program if you don't have a strong math background.   There aren't a lot of math people on this forum but you can go to mathematicsgre.com and ask on there.  It might be better to wait a year do well in real analysis and apply for programs for fall 2019.  I think an A in real analysis could really improve your chances at both the MS and PhD level. 

I don't think that you need TOEFL score if you did your undergrad in the States, even if you are not done. You have high grades in upper level math courses so your occasional lower grades won't matter much. Most departments don't care about your GRE verbal and writing unless you really bombed it. 154 verbal is a respectable score and you will be fine with that score. Your overall profile is very strong and I think your lists are fine. Most top phd programs admit a lot of international students, what they really care about is that if you have the potential to make contribution in this field. That being said, they would prefer a qualifed international student than a mediocre domestic student. 

It's hard to give numbers to these, since the importance is very context-dependent. For example, if someone has taken (and done well in) a number of advanced mathematics courses, then a B- (say) in Calc 3 or Linear Algebra isn't a big deal. On the other hand, if that's the most advanced math on your transcript, then it's much more of a concern. 
Some general rules, though:
- The real analysis grade is very important, particularly if it's your most advanced class. It's not uncommon to see students with high grades in Calc and Linear Algebra get a low grade in RA, so if you do well that will help you. 
- Other pure/advanced math courses play a similar role to analysis; so, for example, getting A's in Abstract Algebra and Topology might help you overcome a lower RA grade.
- Statistics courses outside of probability and math stat don't carry much weight, whether they're taken at the undergraduate or graduate level. The one exception is for students who are doing a Masters (or taking Masters-level courses) at a highly-ranked program.
- Non-math quantitative courses can help bolster your application if you're light on math; otherwise, they don't carry much weight.
- Electives courses generally don't matter much unless there is something very concerning there; for instance, you got low grades in all the classes that involved writing.

Well, the first round of application deadlines has come and gone, and soon your applications will be in the hands of admissions committees at programs around the country. From the outside, the process likely seems pretty mysterious, so I thought I would give an overview of how I review PhD applications. 
DISCLAIMER #1: My approach does not necessarily reflect how other admissions committee members perform their reviews.
DISCLAIMER #2: This description applies to PhD applications, where the goal is to identify and rank the most promising applicants; the process is different for Masters admissions, where the goal is to figure out whether applicants meet a given standard.
- The process begins when we receive a list of applicants whose applications are ready to be reviewed (i.e., they are sufficiently "complete"). For each applicant, we typically have access to individual documents (transcript, letters, research statement, etc.) along with a combined PDF file that has all the relevant information.
- First, I get a feel for what type of applicant this is. There are five common types: domestic students coming from undergrad, domestic students attending Masters programs, international students attending US undergrads, international students attending US masters programs, and international students attending undergrad in their home country. I'll also note the institution(s) attend(ed). This sets the expectation for what I will be looking for in the application.
- Next, I'm likely to notice standardized test scores. Both are going to help me start forming my impression of your application.  Basically, I'm looking for anything concerning (e.g., a low GRE quant score) or particularly impressive (a high verbal and/or analytical writing score); if they're in the "solid" range, I don't pay much attention to specific numbers or percentiles.
- One of the things I pay closest attention to is the transcript. I'll start by doing a quick scan to get a rough sense of overall performance; then I'll look more carefully at the courses. I'll start by looking at how many math courses were taken, and how well the applicant did in them. If there are some lower grades on the transcript, I'm interested to see whether they're mostly in "heavier" courses (such as organic chemistry) or "lighter" ones. In evaluating the transcript, I very much keep in mind the institution attended; if I've never heard of a school (and I've heard of a lot of schools, through my experience in admissions), anything less than a near-perfect GPA is likely going to be an issue, and conversely, if an institution is known for grade deflation, a lower GPA might not be fatal. 
- At this point, if there is anything unusual in the transcript or the rest of the application that seems to beg for an explanation, I'll take a look at the personal statement. Otherwise, I'm unlikely to give it much more than a quick glance.
- Last come the letters of recommendation. The vast, vast majority of them are quite positive, so I am looking both for subtleties in tone ("this student was great!" vs. "this student was A-MA-ZING!") and for specific distinguishing details ("this student received the highest grade in my class, by a mile" or "within 3 months of starting to work with me, this student was operating at the level of a PhD student") that add information beyond what I already got from the transcript and test scores. I pay some attention to the academic rank and seniority of the letter writer (the statement "this is the best student I've ever worked with" means more coming from a senior full professor than a second-year assistant prof), but don't recognize most of the names so am not often "impressed" by the stature of letter writers.
- Now, it comes time to score the application. At our institution, we use a categorical scoring system with options ranging from "I strongly object to admitting this applicant" to "I strongly support admitting this applicant". In assigning the score, I keep in mind the total number of people we are likely to admit (which is determined by projected available funding, and discussed before admissions decisions are made), and I try to give "supportive" scores to about this number of applicants. I keep a mental note of applicants that I'd like to discuss with the full admissions committee, particularly if I suspect my score is likely to be substantially higher than my colleagues'.
- The last step involves the admissions committee discussing scores and ranking applicants. Our initial ranking is based on the average score assigned by committee members, and from this we can usually identify some "obvious" admits and rejects. Then, we discuss the remaining applicants and determine our final ordering. 

I don't think that you need TOEFL score if you did your undergrad in the States, even if you are not done. You have high grades in upper level math courses so your occasional lower grades won't matter much. Most departments don't care about your GRE verbal and writing unless you really bombed it. 154 verbal is a respectable score and you will be fine with that score. Your overall profile is very strong and I think your lists are fine. Most top phd programs admit a lot of international students, what they really care about is that if you have the potential to make contribution in this field. That being said, they would prefer a qualifed international student than a mediocre domestic student. 

I am also an applicant so I am not an expert.  I have however read the applicant profiles for the past few years and studied the results survey.  
I don't understand the GPA scale so I can't comment on that. Your math grades are good.  Your GRE quant score is perfect which is great, but your verbal and AWA is a little low for an international student applying to top programs.  There is a thread dedicated to the relative unimportance of SOP for stats programs at the top of the forum.  If you are applying for programs in this cycle I don't know how you can get meaningful research experience in a month or two.   Your list is long but it consists of mainly top programs.  A lot of the schools on your list (WashU, Columbia,  etc.) highly suggest the Math GRE but it is too late for you to take it for this cycle.  Your current lack of a TOEFL score may exclude you from most programs.  Take the TOEFL ASAP if you are applying for this cycle.   Almost all of the schools on your list are highly competitive, especially for international students.   Consider adding some less competitive programs to your list and removing those which have early deadlines and require the TOEFL.   If you don't have a valid TOEFL by the deadline it is probably not worth applying since some programs can not accept you without a TOEFL above the threshold.  Read up on the TOEFL requirements before you submit the application.   Some schools with later deadlines include:  Florida State (2/1),  Kansas State (1/15),  Missouri (1/15),  Baylor (1/15),  Virginia Tech (1/15).   If you don't require funding consider applying to MS programs they have later deadlines and are less competitive.  You could apply to PhD programs after you get a US Masters.