StatPhD2014

This is not even close. The MA at Columbia has a reputation as a way to make $ for the school and is not on par with their PhD program. The Chicago master's is probably the best in the country along with Stanford.  Unless you really want to live in New York, this is a no-brainer. 

I always thought the bigger bias would be that people who were accepted were more likely to post their results

A few thoughts:
 
1. Most epidemiologists spend their time designing, carrying out, and analyzing data from obervational studies and randomized trials. A much smaller group does "epi methods" -- essentially developing new strategies for designing and analyzing studies -- but a good fraction of these folks weren't trained as epidemiologists but rather as (bio)statisticians/mathematicians.
 
2. Unlike math/stat/biostat, epidemiology PhD programs typically want students entering the program to have completed a Masters degree (typically an MPH) first. The reason is that Epi PhD students are expected to have a "shovel-ready" idea for a dissertation when they step on campus, and undergraduate students typically haven't had enough "real-world" experience to develop a specific research question that they want to investigate. 
 
3. In comparison to PhD programs in math/stat/biostat, Epi PhD students typically have much more limited quantitative background. I doubt that there are more than a handful a Epi PhD programs where the average quantitative GRE score is above the 80th percentile. 
 
4. Unless you know the precise sub-field of epidemiology you plan on pursuing (e.g., infectious disease epidemiology, where a couple of molecular biology courses might be helpful), it's hard to justify taking a lot of bio/chem classes. I get the impression that most epidemiologists become interested in a particular area during their Masters/work experience and then pick up the biomedical background they need along the way.
 
5. It would appear that Northwestern has a one-year Masters program in Epidemiology and Biostatistics (http://www.publichealth.northwestern.edu/prospective-students/mseb.html). Wouldn't that be more relevant than Applied Math?

Do you really expect us to have any idea

Come on half of those words are not difficult at all, for example "heretic", do people really not know what that means by the time they graduate from college. These guides suggest to study vocab words because it is an easy way to improve your score, i am not saying that it doesnt improve. Just that you can still get a great score with an above average vocab especially since so many international students take the test, american students already have a huge advantage there in terms of percentiles. If you have great reasoning skills an average vocab will be sufficient for this test, if not then studying vocab words will be necessary. The reading comprehension should be accesible to most domestic students not really any difficult words there.
 
Also only a small percentage of sentence completion and equivalence questions have words that are unreasonable, luckily the verbal section has a long tail. For example a 720 when i took it was in the 98th percentile, so you can still get a good amount of questions wrong (as compared to the quantitative section where the scoring is a lot more unforgiving). Now if you are scoring in the middle or towards the upper middle getting those tough vocab questions correct will definitely improve your score, but given the way the scoring works you can get those wrong and get all the reasoning questions correct and end up with a great score

You don't need to ask about your application in general or lead off with it. If they have done admissions ask them what they look for in a candidate in terms of grades, strength of undergrad insitution, importance of research (for example can it overcome poor  or less than stellar performance in coursework), after this you can ask some questions specific to your situation. For example in Stats some departments such as Columbia or Uchicago highly recommend the Math subject test, but that is actually a means for them to gather more information about your math background. If you went to a top 10 university, and had a great GPA in mathm then the subject test becomes irrelevant for them

Again, you're comparing apple's and oranges here. Top liberal arts colleges, say your Haverford's and Swarthmore's are in a very different class than a commuter school with low research activity. You also seem to be intentionally ignoring the fact that aside from Princeton, the "elite" privates are known for having some of the worst grad inflation. I don't think a student in the top 5% of their class from a large public university with multiple presentations and 1-2 years of research experience is going to be at a disadvantage applying to grad school. In fact, I am counting on this myself and the feedback I have gotten from top programs has been very positive thus far. That said, I really only have experience in my discipline, things could be very different for other disciplines but I know plenty of people that have had no problem making the jump from lower ranked schools if they have well defined research interests and quality experience.

Do you really expect us to have any idea

Well, I'm not saying that having an advanced degree hurts. My experience has been that connections predominate everything else in terms of getting hired. And if a group's managing director went to NYU Stern and you've got an NYU MFE Master's you'll be looked kindly upon.
 
There are groups and functions within the banks that want MFEs, math PhDs, physics PhDs and so forth. These groups are mainly [Note: I use 'guys' to mean 'guys or girls'] (1) programmers (who write the risk models, electronic trading algorithms, etc.); (2) structured products guys (who put together portfolios of diverse securities tailor-made to a client's risk/return/exposure needs); (3) highly quantitative research guys (who develop proprietary risk-analysis or screening methodologies...though frankly these are a dime a dozen); (4) quantitative risk-management guys (who slice-and-dice the firm's risk exposure, analyze it, stress it, and present the results to management).
 
And even groups in these roles regularly take in candidates without the requisite education and train them up themselves.
 
That said, the vast majority of roles do not require an advanced degree. A typical research analyst uses a pretty basic balance-sheet Excel model, screens for leveraged buy-out candidates with simple rules-of-thumb, and so forth. A typical strategy research analyst uses straightforward regression at most. Real front-office 'revenue generators' (traders, salespeople, investment bankers, etc.) do not need any special training. The banks care primarily about experience...and I can say from personal experience that that's the most important predictor of success in the financial industry. Much of the knowledge required and used here is highly specialized - and the degree of pressure is high. I don't think you'll be able to prepare for it without having to go through the crucible of experience.
 
However, a master's or PhD certainly doesn't hurt. One of the most successful junior salesmen on my desk has an Econometrics MS: a degree he emphasizes is totally worthless. Incidentally, his comments about his job may be relevant: 'How much do I like what I do at work? 3 out of 10. How well-compensated do I think I am for the work I do? 9 out of 10.'

It doesnt really matter if they remember you , it depends on the course you took with them was it a high level difficult course? if so getting an A in such a class will get you a good recommendation if you took the class at a top university

yeah dont bother taking the subject test, its a hard test and with your background you will have a tough time getting a decent score you'll gain a lot more and spend less effort by taking real analysis and probability. who are you planning to ask for recommendations that maybe an obstacle for you

yeah dont bother taking the subject test, its a hard test and with your background you will have a tough time getting a decent score you'll gain a lot more and spend less effort by taking real analysis and probability. who are you planning to ask for recommendations that maybe an obstacle for you

I kind of agree that when I see a comment that comes across as exceptionally entitled, I can guess it has an "I" next to it.  You also have to keep in mind that the competition for international slots at the top schools is so ridiculously tough that if they believe they have a shot then they probably have not encountered much failure in life.  Plenty of international applicants have done everything right and yet find themselves locked out when objectively less qualified domestic applicants get in.  That can't feel good.  The other reason might be that readers are more sensitive to connotations and word choice when something might be construed as boasting.  Here, the language barrier might be leading native speakers to misinterpret the tone and intent.  For example, I knew ahead of time from discussions with adcom members that I was probably going to get into Michigan's program, but I would never say I "expected" to get in because I know that it sounds annoying and arrogant when I simply want to convey that at some point I had prior knowledge that it was likely to occur.  Even now I feel uncomfortable having typed out those words because I understand the connotation.  Since 99% of the international students I know are exceptionally humble and gracious, I am inclined to think the occasional grating entitlement in the results survey is just a combination of poor word choice and frustration at a particularly dark moment.

Ask this topic to the faculty of both of these schools, or ask the professors at your undergraduate institution. Do you really want advice for this kind of decision to come from an anonymous forum?

Ask this topic to the faculty of both of these schools, or ask the professors at your undergraduate institution. Do you really want advice for this kind of decision to come from an anonymous forum?

The point of a lot of my previous posts is that it's a combination of factors which make a successful applicant. There are very few "perfect" applicants, so we end up balancing each applicant's strengths and weaknesses. Great letters can make up for a lower GPA (within reason), mediocre test scores might give some people pause even if grades and letters are strong, lots of good grades in rigorous math courses can sometimes overcome unexciting letters, etc. No one factor dominates.

StatPhD2014:
 
The GSS adviser informed me that they sent out a few acceptances last week but that a final decision has not been made on a small number of applications, including mine. So your application might still be in the running for consideration. Do not lose hope! So it sounds like Berkeley is NOT finished sending acceptances and rejections yet.
 
I am frankly shocked that I have not been rejected yet, to say the least. No complaints here though, haha.

I contacted the chair an hour ago. He replied to me that he is not in the loop on admissions and cc'd the GSS advisor within two minutes asking her to give me a status.

Came across this while looking at Twitter, thought these might be helpful to people looking to compare departments. I hadn't seen current data for the number of graduates (I think NRC uses numbers from 2005), so some of these figures from 2010-2012 were pretty surprising to me.
 
Texas A&M is the second largest producer of stats PhDs after NC State, who knew? Columbia graduated 288 stats MA students alone in 2012 -- that is, over 100 more students than the total biostatistics PhDs awarded in 2012 across all US departments!
 
Largest PhD programs in statistics and biostatistics
 
Largest master's programs in statistics and biostatistics
 
If you follow the links above to the AmStat blog posts, there are links to PDFs with a complete listing of annual number of graduates by year from each program.

Hello some of you might be interested in this, I have scraped the admissions data for statistics phds/masters from the grad cafe. The csv file can be gotten here. The python code used to generate it is here.
 
The code could be easily modified to get biostatistics, or math, or any other subject, data too.
 
The most annoying part is that schools have many names given for them, I have collected a list of synonyms, but in the future, if you run the code again, no doubt new cases will arise, and you will have to add these to the list in the code.
 
If you run the code, it will take about 3 minutes to finish. This is because I have added delays between sending requests to the grad cafe for pages in order not to annoy them.
 
In the code I have added a couple of plotting functions the most basic tasks.

 
Things that could be added
I have only collected records that are accepted/rejected, could add wait listed and interview as results. Could add data about schools from the usa today rankings or NRC. Standardising gre data/ from 160 to 900 scale, also people report as percentages, esp for subject gre. I hope those of you who are data-curious will find some interesting things out and share them with us.

I always thought the bigger bias would be that people who were accepted were more likely to post their results

Where can i find these admissions rates, do you a link to it i would be interested

To answer some of your questions, here's how we do things in my department. I would expect that things are not too different elsewhere:
 
- The admissions committee is composed of about 5 faculty.
- All members read each PhD application; there is no "pre-filtering", though it's unlikely your application will be read in great detail if your "top-line" numbers (GPA, GRE, TOEFL for international students) are way out of line with department norms. We receive translations of international transcripts, and can usually get a decent handle on how good these students are.
-  Some number of applicants are "obvious admits", their profiles being simply outstanding in all or most respects. Usually these "slam dunks" occupy about 20-40% of the offered spots. The "good" and "very good" applicants compete for the remaining spots.
- After scoring the applicants, the committee meets to focus on the applicants who are "in the discussion" for PhD admission. Factors working in favor of (e.g., really positive letters) and against (e.g., lower grade in an advanced math class) each applicant are discussed and weighed. Sometimes, a faculty member will "go to bat" for a student they think highly of, even if that student ranked a bit lower in the initial scoring.
- As I've noted before, applicants worry way too much about research experience and the personal statement. This is not to say that having research experience isn't helpful, or that a strong personal statement isn't an asset, but rather that it is generally much easier (and, in my opinion, more reliable) to rank applicants based on other factors like grades and letters of recommendation. This is particularly true in stat/biostat, where meaningful research experience is relatively rare and it's considered completely acceptable for incoming PhD students to not have much of an idea what they'd like to do research on. 
 
Overall, the process really isn't that mysterious: we are trying to identify the most talented students, with an eye towards balancing research "upside" with likelihood of success in the program. The strongest predictors of success in graduate school remain grades, letters of recommendation, and to a lesser extent standardized test scores. Nobody wants to hear that because applicants would like to think that they can dramatically alter their prospects by crafting the perfect personal statement, but the reality is that your fate is mostly sealed by the time you come to prepare your application.
 
A lot of people contend that "admissions is a crapshoot," but that attitude is simply inconsistent with the remarkably high intra-individual correlation observed in individual admissions results across programs. With a few exceptions, an applicant who applies to a set of schools of similar strength is likely to get into either all/most of them or none of them.