wine in coffee cups

I don't think the OP's coursework being insufficient is a well-founded point of criticism. I had a (pure) math major background with just a handful of undergrad statistics classes and never took any of the courses you listed. Mine were all at a liberal arts college, nothing at a graduate level. I had no problems getting taken seriously by top stats departments this year. I'm sure having some relevant coursework is important but I think only up to a point. Certainly agree that the D- thing and the dropout thing are problematic, hard to guess how much of a risk programs would be willing to take on someone with that history. No specific suggestions for places to apply except to cast a wide net and to talk to your recommenders about things they might be able to mention that would instill more confidence in your ability to succeed in a graduate program. Wishing you the best of luck, econ_to_stats.

Agreed with Quant_Liz_Lemon that econ is crazy competitive, Columbia's econ PhD has about a 2% acceptance rate. You have pretty much no shot with those grades and without having any relevant coursework. EESC requires a year each of chemistry, physics, and earth sciences with B's or better. I don't know how selective that program is or if you have more to your background in those disciplines than just your interest stated here, but do you meet those minimum coursework and grade requirements? Statistics seems to be the most reasonable of the three in terms of what you are qualified for. I can't remember if I saw/heard any acceptance rates when I was considering Columbia stats earlier this year, but I'd be surprised if it was more than 20% or so (potentially closer to 5% if comparable to, say, Duke or Northwestern in selectivity), so I'd still very much consider it a reach. Your research interests sound like a reasonable fit for the department if that's what you want to stick with, at least.

LOL at my rambling emodump post being described as "thoughtful", you are too charitable. I'm not sure that any of your concerns are founded enough at this stage to be a solid basis for dropping programs off your list -- cross those bridges when you get there, you know? Especially large size/attrition considerations, those are better evaluated in person by talking to current students if you get in. In my experience applying last year, I wish I had been a little more discerning about personal/research fit and not applied to a couple of the programs I did that had good overall reputations but didn't make sense for me. I found the statements of purpose for those places frustrating to write and hard to make a case for why I want to go there...pretttttty much because I didn't actually want to go there. cyberwulf has mentioned before that he doesn't think trying to target stat/biostat programs primarily is the best approach and instead to consider overall strong departments. While I can't disagree with the notions that people change interests or sometimes can't get an accurately informed perspective (terrible websites, outdated information, naivete), I think the process is less stressful if you don't try to force something that you just can't get excited about. My recommendation is more or less split the difference to balance your long-term goal of going somewhere sweet with your short-term goal of surviving the process: take a long list of reasonably reputable departments, drop off ones in locations you would never realistically consider, and then further winnow down based on (i) do they have at least a couple faculty there who work on topics you are interested in and (ii) does the department have the breadth to continue to be a good fit should your interests change. Given your qualifications and interests, I think your current list is pretty good, but there is always room for tweaking. I had applied to a lot of those same departments. You might consider CMU. I'd lean Michigan over Wisconsin (though you could apply to both obviously). I recommend making a list of faculty at each place who you'd be interested in working with and noting specifically why that is the case as you add/drop because it will make the "Why ______?" paragraph in your statements much easier.

So to be clear, you aren't really asking if you can do better than #14. My reaction to that question was sure, #9 or #12 or whatever don't sound out of reach if you've hit #14 already and since then improved your profile a bit. However, what you're actually asking is much less reasonable. You're wondering very specifically if you can get into one of the top 3 CS departments or Harvard. I think it's a long shot given you didn't get in last year -- don't these applications ask if you've applied before and sometimes even discourage reapplications? -- and you think your CS research experience is still weak. But you seem like you really don't want to go to UCSD or UCLA (or at least longer than one year) and are looking for an excuse not to. I do feel that you shouldn't go somewhere you have so many reservations about, even if those reservations appear to stem from your fixation on getting into a program that sounds as prestigious to a layman as it is in the CS world. Hey, all those students at UCSD whose qualifications you admire? (1) Yes, this is a reflection of the fact that UCSD is a very good department, but also consider that (2) those students by and large didn't get into Stanford/MIT/Cal or else they'd be probably be there. That would be because those particular departments are extraordinarily selective. Overall, I say reapply, unlikely as it is to work out as desired, but that's because it just seems there's no way you'll contentedly attend one of the very good schools you've already gotten into without starting a few more of these threads. Maybe it'll work out! But probably not. What will you do if you don't get into one of your dream CS PhD programs? I still stand by and killing it in B-school apps in a few years instead. Also, you should definitely read written by a fresh Stanford CS PhD about his experiences. Spoiler: opportunities are what you make of them and just because you're at the #1 department in the world doesn't mean everything will go as hoped. Shit's hard.

This is correct. The percentile you see on the original paper copy of your scores is not necessarily the percentile that you'll see if you check your scores online right now or the percentile reported when you send scores to schools. Percentile adjustments are applied broadly, not just to a group of very recent test takers. People who took the test a little while ago and had an acceptable percentile at the time might be in for a nasty surprise. My subject test result was adjusted down by 5 percentiles in the four years since I took it, and my analytical writing was adjusted up by 5 percentiles over the course of a few months last year. In both cases, the percentile shown online (and what I assume was sent to schools) is not what was on the original paper report, though the scores remained the same.

Just did some browsing of the comments in the results database in the past year for stat/biostat PhD programs that offer no/untenably low funding to least some admitted students: SUNY Buffalo, biostats Rutgers, stats University of Missouri, Columbia, stats (low funding, $8K) Pittsburgh, stats George Washington, stats George Washington, biostats Johns Hopkins, applied math and statistics (accepted a student but waitlisted for funding) SUNY Stony Brook, applied math and statistics UT Dallas, stats So, maybe don't count on any of these programs as viable options even if you think you have a decent chance of admission. GW and SUNY Stony Brook seemed to have the most consistent issues with funding in my perusal of the database.

A lot of the entry-level positions I'm thinking of have "analyst" or "researcher" somewhere in the job title, much along the lines of the roles you describe. The people I'm thinking of have mostly been out of college for 3 or 4 years. Some before mid 2008, some after, but most people with some respectable level of quant skills (including some whose majored in polisci) still found something reasonably interesting and adequately compensated. Off the top of my head, strategy consulting, market research (both in-house and agency roles), finance, healthcare, economic/litigation consulting, political strategy, education or public policy consulting, roles at non-profits -- many places one can look even without a master's. These industries also happen to be concentrated in NYC/DC/Boston. Generally having a statistics class or two and familiarity with a programming language (and comfort learning others) is about all the background these kind of quantitative analyst jobs actually need. Oh, I guess being good at Excel is more useful than programming for some of the less, er, methodology-oriented roles. I think a lot of places ask for 2-3 years experience but don't necessarily mean it -- honestly, I would apply anyway in many cases. Same goes with mentions of particular software/languages. Sometimes they mean it, but often they don't actually care and will hire someone who seems like a quick learner and can pick it up without sucking up too much training time. On the employer side, one of the annoyances in hiring for entry-level analyst positions is that it turns out a lot of people with decent technical chops completely suck at managing details or sharing findings. Employers will be wary of hiring someone who hasn't actually proven that they can run an analysis correctly and present results clearly. Having a fairly significant data analysis project or two under your belt (maybe from an internship, being a research assistant to a professor, senior thesis, or even a class project if you're reaching) will alleviate that concern. The more responsibility you had and the higher the stakes if you messed up, the more convincing a substitute for actual work experience.

Agreed, I find this justification surprising and not in line with my experience. I've never addressed my bosses or clients by anything other than their first names, including in my current job where many hold PhDs. Medicine is the only non-academic field I know of in which people regularly use titles instead of first names to refer to supervisors/colleagues -- even lawyers rarely do outside of formal proceedings. I don't think this is actually an issue of supervisory relationships. I think it's really just people with a lot of education maintaining rather antiquated formalities.

I would go for the implied but maybe unrealized third option: apply directly for quantitative jobs near the end of this second bachelor's. What sort of "quantitative jobs" did you have in mind? I know the economy isn't great, but most people I know with the kind of interests and coursework you have are doing decently job-wise without additional schooling. That would also get your started on the experience needed for a business-related program if you have that as a goal. Of course, maybe you'd turn out perfectly happy to "just" work in an interesting quantitative role and be right at your end goal. I will say, it would be good for all of your potential paths if you got a programming class in there, maybe instead of differential equations.

I think you might be selling yourself short. Yes, your GPA is going to be below average for the top PhD programs, but it sounds like you have good research experience and better than average math preparation given that you're a math major. Is your GPA in just math/statistics prerequisite courses higher than your overall GPA, or maybe you have an upward trend in grades? Does the small private school you attend have a good academic reputation? Maybe you should apply to a mix of master's and PhD programs, and indicate on your applications when possible that you'd like to be considered for a master's if denied for the PhD. I'm no expert but your list of places for a master's sounds reasonable enough. Have you asked the faculty at your undergrad institution or any of the other biostatisticians you've worked with for advice on where to apply? FYI, there is tons of advice regarding biostats in the Mathematics & Statistics forum. One regular poster, cyberwulf, is on the faculty of a biostatistics department and consistently posts helpful information, for example

math_hopeful, I think your third letter ought to come from faculty, not a grad student, as I've seen application instructions be specific on this point. I would consult with the professor who knows your background the best for advice about how to proceed with a third letter. Feel free to write about that independent study in your essay, though. You might be able to pull some nice anecdotes out of that experience to give admissions committees a clearer sense of your interests in applied math. What you believe the other two letters will say -- that you're a hard worker who has exceeded expectations based on your previous grades -- I would think that is not compelling for more selective programs, but may be a good enough endorsement for where you are applying. R Deckard and ANDS! disagree on what constitutes an excellent letter of recommendation, but I think they might both agree on this basic point:* you're aiming relatively low so you don't need letters saying you were the most amazing researcher ever, and people with just okay letters can still get in somewhere. I do think it might be helpful if your letters could give more context to your situation than just pointing to the simple upward trend that is readily apparent from your transcripts. GRE general scores don't usually do much to help as opposed to hurt your chances, but I suspect you'll stand a much better chance with that GPA if you perform well on that test, so get cracking on studying if you haven't already. A lot of graduate schools will have a blanket rule that your GPA needs to be above 2.75 or 3.0, so be mindful of those requirements as you make your list. Best of luck! * I would caveat the advice of everyone here (besides cyberwulf since he's faculty) that we are just guessing about LORs, anyway, since it's rather uncommon for applicants to actually see them, let alone learn how they were perceived by admissions folks.

Here are some GRE averages for biostats programs that might help you ballpark, though these combine master's and PhD and are among the top programs so not a ton of added information: University of Minnesota, biostatistics, admitted students: 575V, 779Q, 3.8W, some more distributional info at the link University of North Carolina, biostatistics, admitted students: 580V, 780Q University of Washington, biostatistics (PDF): matriculated students 618V, 793Q; other accepted students 621V, 794Q; denied students 544V, 771Q UC Berkeley, biostatistics, admitted students: M.A. 680V, 790Q; PhD 620V, 790Q

So what have you done professionally so far? Initial suggestion is to consider a master's in statistics.

Except she is not of Asian ancestry.

Most of the schools I know of that post data have already been identified, but University of Minnesota is one more. It's also amazingly extreme in terms of international applications for graduate CS. Do the math and you'll see 93% (1025/1101) of applications are international, and admit rates are 19% (199/1025) international and 75% (57/76) domestic. Quite the disparity!

This might sound a little weird, bear with me. Have you considered pressing pause on going back to school and maybe applying for, like, a job at Goldman Sachs or McKinsey or some other "elite" employer? I'm getting the sense that you really value prestige, both in and in responding to it in others (#entry1057863770). You what you want to do To me, it sounds like you would get the most personal fulfillment out of working at a status-obsessed place like GS where you can hobnob with a bunch of Ivy League alumni, make a ton of money living in a big city of your choosing, and set yourself on track to attend the name brand business school of your dreams. This wouldn't require nearly the degree of focus and commitment that a PhD would and would keep a lot of doors open for you afterwards. You are pushing all the hiring buttons of those top financial and consulting firms: female, marathon runner, math/CS major from an expensive private university people have heard of, lots of confusingly unrelated but prestigious-sounding research opportunities, previous liberal arts education. You totally have the skill set they are looking for: programming experience, data analysis, striving tendencies. After just a couple of years, you'd be almost assured of getting into at least some of HBS, Stanford, Wharton, Sloan, or Booth. Everyone you'd be around would validate you in all the ways you like to be validated. Is this plan not a much better fit for your personality and goals than slogging away at PhD from a public school in a city you are not 100% thrilled with working on an area of research you aren't fully invested in with an advisor you turn out to hate?

My current work signature follows the company template: name, position, company, firm description, mailing address, landline, fax number (lol), mobile phone, email, firm website, and a 79 word legal disclaimer. Looking forward to not using a signature anymore!

You already have a master's in stats and are looking for another master's? I'm not sure that stats master's programs would be willing to accept an applicant who already has the degree they would award. This is something for you to investigate before you go down this road. But let's step back. I'm sorry to hear PhD applications did not go as hoped for this year. Why do you think that was? And what specifically about an additional master's degree would rectify those particular deficiencies in your application, since it sounds like your coursework is already good?

Maybe? I had taken most of the math courses offered by my college and graduated with a transcript looking just like those of my pure math PhD-bound peers. I did surprisingly well in my applications and sent only one subject score, so perhaps you're right. It makes sense that admissions committees might want other evidence of mathematical competence--like the subject GRE--if your formal training is thin.

I hate to be a big B about this but you are frighteningly wrong on just about every point: I am not aware of government grants for professional graduate programs. Individual schools might offer limited partial scholarships, though you will have trouble qualifying for those with a 3.2 GPA. You will most likely qualify for government loans (Stafford, Grad PLUS) but you will probably find yourself needing to take out private loans as well and having a balance of about $350K between law school in NYC and a private business school unless you get serious tuition discounts. As mentioned above by Spore and pinkrobot, you don't leave law school with a master's. You leave with a JD, the D of which stands for 'doctor'. Know what you're getting into! The JD is an interesting degree in that receiving it can actually make you less employable in all other fields besides legal work if you don't have serious work experience. I think you might be thinking of this simplistically as BA + JD > BA (okay, well maybe you were mistakenly thinking BA + legal MA > BA) which is not usually true. I would be shocked if a JD were viewed as an meaningful asset in broadcast journalism hiring. Good (and even most not-good) MBA programs require several years of full-time work experience. You are extremely unlikely to get in with only some internships from undergrad and law school. The JD won't give you an edge over people who have actual experience. If your goal is to work in broadcast journalism, I think your current plan is a really bad idea. The fact that you wouldn't be able to pay off all this debt on a broadcast journalism salary should be a huge red flag, for starters. Talk to alumni from your program who are working in your dream positions and find out how they got there. I'm going to guess it involved many years of working in the field, not taking on staggering amounts of non-dischargeable student loan debt for unrelated professional degrees.

You do realize that law school in NYC followed by an MBA is probably going to leave you roughly $350K in debt? You're only going to be able to pay that off by inventing the next Facebook, in which case you didn't really need either degree. As for how competitive you would be if you do pursue this wildly impractical dream: check the GPA x LSAT graphs for individual schools on lawschoolnumbers.com.

Any track record from other students at your school applying to stats programs with similar grades?

How did you go about picking these programs? I wouldn't add/remove based on selectivity or rankings so much as research fit. Yale is pretty small, for instance -- sure you want to bother with that one? I'd recommend starting a document where you go through each of these programs, list faculty whose research you find interesting, pick out any special features of the program that you like (e.g. formal concentrations), and then drop off any schools in which you struggled to find aspects that fit with your interests.

You were concerned earlier that UIUC was encouraging you to apply when you had no chance coming from your school just so they can keep their number of rejections high. You do realize explicitly discouraging reapplications is evidence against this position? Demonstrably (Well, not the message board part.)

No, your argument does not make sense because unlike law school rankings, US News rankings of graduate CS programs don't take acceptance rates into account. US News rankings are based just on reputation survey results so there aren't even any objective inputs for UIUC CS to manipulate if it wanted to look better.