cyberwulf

What? Did I scare everyone off? Seriously, if you're using the term "wordsmithing" in relation to your SOP, you're spending too much time on it.

It's illegal for universities to consider applicant age as a factor in making admissions decisions, and institutions generally take this pretty seriously, so I wouldn't worry too much about your age preventing you from getting into a program. And while it would be hard to prove age discrimination if a company (say) chose not to interview, I think that your age is relatively unlikely to play heavily into your job prospects. It's not like you're approaching retirement age, and few companies view MS-level stat analyst positions as "jobs for life" anyhow. You might even bring skills to the table (writing/communication ability, interpersonal skills, etc.) which are in short supply among younger graduates.

If you graduate with anything approaching a 3.9 overall in math from a top 15 liberal arts college, you will be given very strong consideration for admission at every biostatistics program in the country. Your math background is likely to be a strength given that you've got two more years of math classes to go, and you're already taking analysis. Don't worry about taking more bio classes; I would lean towards more math/stat classes instead. Landing an REU would be nice as it would give you some additional perspective on the field and (hopefully) produce a letter of recommendation speaking to your research potential, but a strong academic record at a highly-regarded institution remains the surest path to admission at top programs. Good luck!

Harvard is going to be a tough nut to crack for an international student. Washington gets a very large number of applicants, and a good fraction of the spots are earmarked for U.S. citizens/permanent residents. Berkeley is such a small program that results can be weird. Of your list, Wisconsin is probably your highest likelihood of admission, closely followed by Michigan, UNC, Minnesota, and Berkeley.

This list of schools is *probably* going to yield a couple of admissions offers for you, but I would still advise adding a handful of somewhat lower-ranked biostat departments (Emory, Columbia, UCLA, Pitt) and/or some of the bigger stat departments (NC State, Iowa State, Ohio State) to give yourself a better safety net.

Yep, fairly strong profile, though you probably have less advanced math than many of the top international students applying. A lot will depend on where you are from; for instance, graduating with a 3.99 from, say, Fudan University in China will put you in excellent shape while if you are from a small country you may have a tougher time. Agree with Shostakovich that the 169/166/3.5 is probably the better score to report, though I don't think the decision is obvious. We see very high GRE verbal scores from international students all the time which don't seem to match their speaking/writing ability, so I (and I would imagine some other faculty) don't put much stock in the score. The TOEFL is a much better indication of language ability. But since 166 and 170 quant scores are essentially indistinguishable, you might as well go with the higher verbal.

6-10 programs is the usual range; what's more interesting is which programs make up the list. It's possible to make a very reasonable list of 5 and a completely crazy list of 15.

My read on LL's disappointing results last year is that programs just didn't find enough in the application to get "excited" about. Doing a Masters gives you multiple opportunities to get faculty excited about your abilities: excellent performance in more advanced courses, top grades on exams, and outstanding contributions to research projects. It's probably best to look for a program where some Masters students go on to do PhDs (vs. one where everyone is going directly into industry), as these departments are more likely to provide the advanced coursework and exposure to research which will pique the interest of PhD adcoms.

Suggest you start a new thread for this.

Ah, yes, the irony indeed. Many SOPs that I see touch on the following points (often in this approximate order): - Why/how you got interested in statistics/biostatistics. - Unusual or particularly challenging circumstances which require explanation (in your case, perhaps a few sentences on why you're leaving finance; for others, this could be significant obstacles faced during undergrad work, etc.) - Relevant experience or background which makes you well prepared for graduate study. - Sub-fields of stat/biostat which you find particularly interesting. - Pointless name-dropping of 2-3 faculty who work in those areas. Seriously, don't try to get fancy or clever, or overthink this.

A Masters from any of the top 10 or so departments will be well respected in industry.

I think the U.S. News provides a pretty good ranking, though you have to spend a few minutes distinguishing stat from biostat. Roughly speaking, the top 10 places are: Harvard Hopkins Washington UNC Michigan Minnesota Berkeley Emory Penn Columbia I think you could also make an argument for departments like UCLA and Brown to show up in the last 2-3 slots.

Things are pretty darn tough for international students these days. I think wine in coffee cups is right about your relative lack of advanced math courses being one reason you failed to crack the top stat programs; a strong Math Subject GRE score could help you on that front. Biostat departments will care less about your math prep, but they tend to value communication/writing skills more highly and also set aside a good fraction of their spots for domestic students, so the bar for international applicants remains quite high. Speaking for biostat, I think that places like Michigan, UNC, Columbia, Minnesota, Emory, Berkeley and Penn are decent options for you; you might not get into all, but I would be surprised if you didn't receive admissions offers from at least a few. Have you considered doing a Masters degree first and using that as a stepping stone to a high-ranked program? Your record is such that you are a lock for admission at virtually every Masters program. Sure, you probably won't have guaranteed funding, but perhaps your letter writers could play their contacts for a suitable RA position? If you were to rock a top MS program, then combined with your undergraduate record I think you would find your chances of admission at good places dramatically increase.

I'm going to disagree with most of the comments above, and say that I think your story definitely has a place in your SOP. Your experience is not commonplace among students applying to grad school (at least in my field, and I can't imagine biology is that different), and writing about it helps put your academic performance (good, bad, or in between) in context. Furthermore, one of the most important traits for grad students to have is the ability to succeed in difficult circumstances, something which you can credibly claim to have demonstrated. Sure, don't make your whole SOP about your personal life, but I think it's worth more than a sentence.

I was taking OP at their word regarding departments listing measure theory as a pre-requisite. I'm not at all surprised to hear that most actually do not require it.

I suspect that the trend is towards "overlooking" lack of a previous measure theory course for otherwise promising applicants. Many departments which are behaving this way may still have it officially listed as a prerequisite, however.

I would try CrossValidated (http://stats.stackexchange.com/).

While this isn't really the place for this type of question, the quick answer is that if X and Y are independent, then the probability that the CI "box" for muX and muY contains both is, indeed, P(CI(X) contains muX) * P(CI(Y) contains muY) = 0.95 * 0.95 = 0.9025. Since you've generated X and Y independently in your simulation, you are getting the expected result. If X and Y are dependent, then the coverage probability of the "box" may not be 0.9025.

Very few people get letters from "well-known" professors. As biostat_prof said, the main issue is the strength of your school and how you compared to other students there. Hopefully, you can get someone to say something like "Vokram8 is a better student than Vokram7, who graduated two years ago and is now a PhD student at [prestigious stat/math program]."

MS and undergrad GPA mean totally different things. A 3.7 MS student is usually about average, so most decent schools look for a 3.9+ Masters GPA, particularly if the program isn't well known.

There's a distinction between someone with a 4.0 and someone with a 3.9, a distinction which is particularly important for top graduate programs: the former student hasn't yet met a course they couldn't ace. Schools are trying to ascertain applicants' upside/potential, and a 4.0 (vs. a 3.9) is a really good indicator that you have a lot of it. I'm genuinely surprised to hear about the GPAs of math majors in the data you analyzed. Regardless, I still think you're overestimating the number of elite applicants; at least in biostat, I can tell you that there are no more than 5-10 with the type of profile you're describing applying in any given year. At our (fairly well-ranked) institution, we probably average 3-5 applicants from the top 20 liberal arts colleges TOTAL. I doubt that the applicant pool in stat is 5-10 times deeper than biostat.

I'm going to quibble with your numbers here: If there are indeed "dozens" of applicants with perfect GPAs from top 50 U.S. schools applying to stats departments, then it would presumably follow that these folks would fill up the top 5-6 departments making it virtually impossible to get in without a perfect academic record. This just isn't what happens, so the number of domestic applicants with records similar to the OP's must be lower, perhaps 10-15 people. Many (probably a majority) of the best math majors at elite schools are applying to *math* PhD programs, with the fraction increasing with school prestige (e.g., a near-4.0 in math from Princeton is probably being strongly encouraged to do a PhD in math because they will have their pick of where to study, whereas a math student with similar GPA from University of Virginia might view stats as a more viable option). Some students presumably go the econ route. So stat only sees a fraction of the top students, perhaps 20-30%. I can believe that there might be "dozens" (perhaps 25-40) of applicants to stats programs with near-perfect GPAs, but the majority of these will be from schools much less prestigious than UNC. Two things: 1) For the OP, I think the SOP actually may play a slightly bigger role than for the typical applicant because of the time spent away from school. It is helpful in such cases to explain what has motivated your change in career trajectory. It may also be an opportunity to say what skills you gained during your time in the "real world" (e.g., applied statistics). My general point in the sticky was that most applicants straight out of undergrad have nothing interesting/useful to say because they have little exposure to statistical research, so they shouldn't worry too much about what they write. And even for the OP, I still contend that the statement will play a minor role, at best, in determining where you get in. Letters will be much more important. 2) Faculty love to think (and say!) that "all our applicants are uniformly superb, so the only way to distinguish between them is the personal statement." But that is just chest-thumping fiction; GPAs, test scores, and letters of recommendation still allow a ranking of candidates that most would agree on. wicc, I don't doubt that faculty you talked to remembered and liked your SOP, but I question whether it really made the difference between acceptance and rejection or whether it merely made your application stand out among the group that was going to be accepted anyway.

DMX, your results last year were pretty surprising to me and not representative of what happens to the typical student with a record like yours (and the OP's). Have you contacted departments to get a sense of why you didn't get in? The only plausible explanation (assuming you're not exaggerating your academic credentials) seems to be a negative letter or something similarly disastrous (e.g., awful TOEFL score if you're a foreign student). A 4.0 math/econ double major from one of the best state universities in the country has the pedigree to be competitive ("in the discussion") for admission at every PhD program in the country. Whether or not such a student cracks the top few departments will depend mostly on the strength of their letters of recommendation. So, OP, I think that Cornell/UNC/Berkeley/Michigan/UW is a good start to a list of places to apply for *PhD* admission! You might want to add some more "local" places like NC State and Duke. Your "safeties" should probably be the Masters programs at these schools, where you're essentially guaranteed to be admitted.

Your only weakness appears to be a lack of statistics coursework. Assuming you have another year of study remaining, I would suggest trying to fit probability and mathematical statistics into your schedule. A real analysis course, while not mandatory, would be a big help as well. With your current record, I think you will have a pretty decent shot at most departments outside the top 3, so I wouldn't be surprised if you had similar results to Igotnothin, above. You've probably got a decent chance at UW, and it wouldn't be crazy to apply to Harvard/JHU.

To get a better sense of your chances, we'll need to know: 1) Whether you're a U.S. citizen/permanent resident or not 2) The (approximate) strength/reputation of your undergraduate institution 3) Which math/stat courses you've taken Your profile as stated seems fairly strong, but the above details could make the difference between you having a decent chance of getting into the top places you applied, and struggling to crack some of the mid-range places on your list.