theduckster

I've been rejected off waitlists twice in past admission cycles, so I know what that is like. That doesn't change the fact that deadlines are in place to protect applicants from being forced into earlier decisions, when they themselves might be waiting for wait list decisions. Comparing me *following the deadline* with being mean to strangers is taking it a bit far, IMHO. Until the last few days, I was waiting to hear from one other program (now I have given up) so I had my reasons for delaying.

No consultant in this world can fix your transcript and LoR, which are the most important components in your applications. Competition among international students has got to a point where top GPA, prestigious undergrad institution and good LoR can only get you into consideration at top schools. They have many people with perfect GPA, so you need extra things to stand out. To be accepted at those schools, you need strong research experience, excellent LoR from well-known professors, and a bit of luck too. I don't see how a consultant can help you with those. If the OP has $3,000 to spend, I would advice him to use that money and apply to 30 schools across the US News ranking. I am sure that he will get into a few places with that GPA, publication and a prestigious MS. He is certainly competitive for top-40 schools.   

dont listen to people who tell you you're not competitive enough to apply to school x. Hire a graduate school admission consultant, about $3000, to help you package your application and shoot for your dream schools. Grad school admission consultants will make sure you take the best swing you can at your dreams. don't shoot your dreams down without giving them a chance to breathe.
Start your grad apps 1 year before the deadlines. It will take a full year if you do it right. Your GPA is stellar for a math degree. Great job on that.

Lol, $3000 for a consultant? I would not listen to this bad advice, OP. Most PhD programs in Statistics in the USA are swamped with international applicants. The top tier programs like Penn, Stanford, and Harvard can take their pick and typically do not consider any applicants who are not from the top 5% of their graduating class at ISI, Peking, Tsinghua, etc. The OP sounds like a strong candidate but the reality for international applicants is they need to be the top students from the most elite schools in their home country in order to have a reasonable shot at these schools (even if they get a Masters degree from a school like Duke in the U.S., that is still not likely enough to overcome the undergrad alma mater issue because graduate school grades are usually more lenient).
We provided the OP with a realistic range of schools they should apply to and even encouraged them to try a few "reach" schools like NCSU (Harvard and Penn Stats would almost certainly be a waste of money though).

You'd probably have a better chance if you had applied to the PhD program, I think.

Didn't get accepted by UChicago for an MS, which is totally fair. But not even being waitlisted despite having As in Real Analysis and Measure Theory, as well as some research experience? Also not shocking, but gotta say that stung a little.
Could it be because I only have one statistics class (Probability Theory)?
Blarg. Life goes on.
 

Didn't get accepted by UChicago for an MS, which is totally fair. But not even being waitlisted despite having As in Real Analysis and Measure Theory, as well as some research experience? Also not shocking, but gotta say that stung a little.
Could it be because I only have one statistics class (Probability Theory)?
Blarg. Life goes on.
 

got an offer from Davis on a Sunday night...

UPenn Wharton is an excellent department and a top 5 one in my personal opinion. They have some great faculty like Tony Cai and Dylan Small. Their main strengths are casual inference, nonparametric/semiparametric regression, and large-scale multiple testing. Their cohort sizes are also small (each year has only 4-5 students), so you'll definitely get to know your professors and form some close friendships in the department.
Also, even though the Statistics Department is housed in the business school, it is actually a primarily theoretical/mathematical department (some very good faculty in pure probability theory, fwiw), and most of the faculty do not do research on applications to business.

Yeah, as long as you don't say that you want to become a drug dealer after you should probably be fine. 

I was admitted to Columbia Statistics! This is my first acceptance of the cycle. Don't lose hope, everyone.

Got my UConn acceptance today!! They must win the record for fastest turnaround, I think that was within 2 weeks.

My wait is over!! I got an acceptance to PSU! No matter what happens now, I'm going to grad school!
This is so exciting - good luck to everyone else!

I have no idea how this happened but I got into University of Washington. I got the email at 12:30am EST after a few glasses of wine and was incredibly confused but so excited.
The good news continued this morning with an acceptance from UCLA.
This is gonna be tough. UW was like my number one school but my wife realllly wants to be in southern California..

@fireuponthedeep I'd be careful about making implications like "PhDs dominate the top of X industry" ==> "Getting a PhD will help me climb up X industry".
Lots of correlation vs. causation issues here, plus confirmation bias. Most billionaires have somewhat eccentric backgrounds, but doesn't mean we should start emulating them in that regard!
The biggest cost with PhD is opportunity cost. Those are six years where, if you had stayed in industry, you could have gained valuable experience, a fair amount of money, and moved up the corporate ladder. But if you truly love research and want a research-based position, then going for a PhD makes complete sense.

Sorry I should have been more clear. I think the wave is just those who got off the waitlist. Our department is relative small (though increasing), but they might have sent out most of their offers in one go (late Jan / early Feb).
Last year, I was one of the 35 accepted students out of over 400 applicants.

Congrats to everyone who has gotten acceptances already, and for those of you who haven't keep your heads up - you'll get them soon!
I have to admit that I am more than a little jealous as an MS applicant that you folks are getting your results in so early

Looks like the subject GRE did not matter that much for Berkeley, though, because I just got in today. I also got into UMichigan.

Has Yale already given offers for MA in Statistics? I saw an acceptance today. I thought I would have a decent chance for masters sigh. thanks.

Congrats to all who got accepted to Stanford! I still haven't heard anything from them. 
However, I woke up to an email this morning from UC Berkeley! I've been accepted!! I'm beyond ecstatic, considering that Berkeley was my top choice school. 

accepted to duke as well just now (no interview)!

I literally just got emailed by Duke to check the application portal, and it was an acceptance letter from the department!!! I am beyond ecstatic, after checking my email almost constantly since last week. This is the first correspondence I've had from Duke (there was no request for an interview or anything like that). 

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. 

As others will tell you, you should always go for the professor/faculty member that has directly worked with you and can say something strong about you. If a letter is just reiterating your transcript or CV, then it will probably be next to useless (unless the letter writer is a really good embellisher).
Just make sure that at least one of your recommenders is a tenure-track professor (or academically-known individual) in a quantitative discipline. It seems like you've already got that covered, so no worries here.

UIUC is very well known by large tech companies. It is a top 5 school in computer science for crying out loud!