Biostat_Assistant_Prof

I'm an older graduate student that serves on my department's admissions committee this year (outside of the top 5 schools, that's all I'll say). Looking over your profile with the information you provided, here are the two big concerns: 1) Your GRE quant score of 148. Yes, it has already been addressed in the above comments, but I'm going to drive the point home... regardless of anything else on your application, a 148 would immediately push your application to the "outright reject" pile in my eyes. As cyberwulf noted, that low score coupled with your extensive background of MS stat/biostat courses and undergraduate math courses is a huge 'red flag', i.e. if you have that much time spent in quantitative courses and still score lower than the 50th percentile on a basic logic/math section of a standardized test ... that's a huge concern. 2) Low 80's and high 70's in your core math classes from undergrad (i.e. calculus, linear algebra, and analysis) are certainly underwhelming. You have extensive statistics coursework under your belt, but from what I can tell, those are mostly applied classes and don't indicate to me you can handle theoretical classes. In a PhD program, you will be expected to work through and understand the theory of it all, requiring strong calculus and linear algebra skills... and this isn't evident. My advice... Get your GRE Quant score up to 160+. If you get your score to 160+, I'd guess you won't be immediately dismissed from some application piles, and personally, I would probably read further into your application, looking at your letters of recommendation and to a lesser extent, your personal statement in this case would be deciding factors to give you a chance for an interview. I would want to see you address your 'subpar' performance in some of those key math classes, and further, with your background, 2 MS degrees and a BS, I would expect you to have 'strong' LoRs. As for target schools, have a look at the following list (I'm copying and pasting directly from this thread, which separates biostat programs based on USNWR rankings). I'll be the first to say that rankings are not important as long as you have a good mentor, but they provide a general list of "competitive" to "least competitive" places you could apply. I'd guess there are an equal number or even more programs in the US that are not listed, and in most cases they would be about as competitive as the lowest schools on this list (minus a few notable exceptions like Vanderbilt, which is a good program, just small and relatively new). If I were you, I'd focus on the schools ranked below 15 on this list and programs that are unranked for your best shot at getting admitted. BIOSTATISTICS 1-2. Harvard, Washington (tied), 3. Johns Hopkins, 4-5. Michigan, UNC-Chapel Hill (tied), 6. UC Berkeley, 7. Minnesota, 8. UPenn, 9-10. Columbia, UCLA (tied), 11. Yale, 12. Emory, 13. Brown, 14-15. Iowa, Rochester (tied), 16. Pittsburgh, 17. Boston University, 18-20. Medical College of Wisconsin, UIllinois-Chicago, UTexas-Houston (tied), 21. Case Western, 22. Medical College of South Carolina, 23-25. SUNY Albany, Alabama, SUNY Buffalo (tied), 26. South Carolina, Virginia Commonwealth

From what I know about UMich is that it is the general policy that you don't get into their PhD program without a masters, but the funded fast-track masters is essentially the same thing as a PhD offer when you come straight from undergrad. I had the same deal a few years ago. I didn't end up there, so maybe some others can chime in, but what I was told was basically that if you pass your first year qualifying exams, it's smooth sailing into the PhD program (i.e. everyone that wants to continue with the PhD after this point will be accepted to do so) With that said, in general, I think both are equally reputable. If absolutely forced to rank one over the other, I have the inclination to give a slight edge to Michigan, but I doubt I could give a convincing argument as to why - it's just my gut feeling about it. I think if stat genetics, genomics, etc. are your interest, UMich would be the better choice. If more clinical oriented statistical methodology (e.g. clinical trial methods) are your interest, UNC is the better place.

Cyberwulf couldn't be more correct in saying "the name of your dissertation advisor matters." Your advisor/mentor is the most important component for success in graduate school! FSU's 'biostatistics' program is housed within it's stats program, whereas the remaining departments you mention are within med schools or departments of public health (as are most biostatistics programs). FSU will be more theoretical; All of the other schools you mentioned will probably give you more/better opportunities to work physicians and lab researchers than will FSU. For clinical trials research, Vanderbilt, MUSC, and UNC all have ties to med schools and hospitals with active clinical trial programs, and biostatistics faculty at each are doing methodological clinical trials research.

Looks like a solid applicant profile from my perspective. Based off of this information, your safety's are definitely safety's, but I would even consider your target schools as pretty solid bets. On top of Harvard and Hopkins, I'd include applications to Washington, Michigan, and UNC, and of those 5, I'd be surprised if you didn't get into at least a few.

US News and World Report ranks statistics and biostatistics programs together. There is a thread somewhere in this forum that teases the biostats programs out of it. it. Generally, everyone tends to look at them in terms of tiers rather than individual rankings. Tier 1 is usually considered Hopkins, Harvard, and Washington, Tier 2 is Michigan, UNC, and Minnesota and arguments could also be made to consider Emory or UC Berkeley into that mix as well. Beyond this, there are rankings, but generally I think this is when it's best to start looking at specific research interests and potential mentors. UCLA would probably be considered by most to be stronger overall than, say, Boston U, but I don't necessarily think choosing UCLA would be the best option for everybody. You would need to consider specific interests and how they match these two programs. The benefit of the top/biggest programs is that there are large number of high quality faculty with diverse research topics, so coming in as a blank slate, your chances of ending up with a strong mentor and project are greater... Smaller departments with newer programs (like Vanderbilt for example) may have fewer faculty members, so you have less options. However, if you're really interested in a specific area that a particular faculty member works in at a smaller/lesser ranked department, it may be the better option. Biostat_Prof has some great comments in past threads about how one's mentor is more important than school rank, and I think they're worth looking up. I remember reading them a few years ago before/right when I started my PhD, and now in my 3rd year, I really understand the truth in everything he said.

Are you asking if a MS from Hopkins/Harvard would be preferred/more prestigious than a PhD from anywhere else? Assuming the PhD is a legitimate PhD from an accredited university, the PhD definitely carries more weight... As for rankings, after you get past the top 10 or so programs, comparisons between schools in terms of rankings are almost meaningless. No matter what program you choose, your PhD adviser is much more important than your school. Especially in the mid-lowest tier schools, specific research interests and specific available mentors/advisers should drive your choice. My opinion, a good advisor at a >10 ranked school is a far better situation to find yourself in than an average/bad advisor at a top ranked program.

UNC, Emory, Brown (grown a lot in recent history), Minnesota ... All have strong biostatistics programs worth looking at

Here are my guesses. Assuming strong grades across Calculus, LA, and Real Analysis... I would say: Harvard MS - Likely BU (PhD assumingly) - Safe bet UNC - Probably... If you're a US resident, then it's closer to likely, and lesser so if you're not.

If you're intelligent enough to handle the math that a masters in stats/biostats requires, you can certainly learn SAS. Seriously, it takes maybe a month or two of regular SAS use to become a reasonably competent SAS programmer, but you'll start getting the hang of it after only a few days. R on the other hand has a steeper learning curve, but is lower level than SAS, more akin to 'traditional' programming. Even though it's primarily built as a statistical analysis software, I'd put the syntax/language of R closer to something like Python. It takes longer to become proficient in R as it requires a more traditional understanding of loops, building functions etc., but can be used for much more in depth analysis. Don't worry though, basic analysis is easy enough in both languages.

TomorrowWorld!!!!! Here is a link to last years aftermovie!

To answer a few of these... Michigan does this for most students without an MS, but I've heard they make exceptions for very strong students (and I think you may qualify as such). However, Michigan funds quite a few MS students at a pretty good stipend (~$27k if remember right, and having gotten that offer myself back when I applied, I can't imagine you won't get it). I'm not exactly sure how much Columbia funds the PhD track MS students, but given cost of living in NYC, I guarantee it's no where near as good as what $27k will get you in Ann Arbor. I will say though, I have it on good word that the students in this certain MS program at Columbia will almost always be accepted to continue on in the PhD program... This next part I'm am far from certain on, but for some reason I want to say the PhD students at Columbia get something like ~$35k/year (idk where I heard this or why this number stands out in my head, so definitely take this with a grain of salt). Look at where the faculty are publishing and the topics they're publishing on. If you see a certain faculty member (or group of faculty) at an institution publishing in journals like JASA, JRSS-B, Biometrika, Annals of Stats, Biostatistics, Biometrics, Stats in Med (those first 4 journals being what I think are generally considered the best) - then whatever the topic they're publishing on is pretty indicative of that departments strength in that area.

I can only speak for Biostats, but I'd say your competitive everywhere you just mentioned (and actually everywhere in general). Honestly, I'd drop BU and Pitt from your list and replace them with Harvard and Hopkins...and I'd be very surprised if you don't get an offer from at least one of the top 3 schools! On another note, Columbia doesn't accept PhD students straight from undergrad... the best you can do at Columbia is go into their accelerated MS track for pre-doctoral students... The funding won't be competitive compared to the other offers you'll get, especially in NYC. Nothing against the program, you'll definitely get in, but I wouldn't even waste the application money to apply there if I were you because it wouldn't be worth it compared to the other places your applying.

It interesting to me - having to think about these types of things that grad students just 10 years ago didn't have to think about. In my department, the "unwritten policy" is that grad students aren't friends with faculty while they remain a student (although it's not technically against any rules or anything). I know once students graduate, they usually become FB friends though. I'm friends on social media with one faculty member in my department, and that's only because when I stared - this person was a student (before being hired as faculty). I have good relationship with my advisor and faculty, and personally would have no issue with being "friends" on social media. I don't post about anything I wouldn't openly admit to anyone, but I get that some people wouldn't want to give their "boss" the ability to peek into their lives outside of academia/work. It's funny, because I'm actually in a small FB group with a number of faculty in my department, and communicate on posts within this group, although we're not technically "friends"

What "Bayessays" said is good advice. Biostatistics programs will be more applied - dissertation work will still be a methodological contribution to the field, but not necsarily a big theoretical contribution (not sure how much that makes sense to someone not in the field yet) . Hopkins and Washington will be more theoretical than most other places - Liang and Zeger's GEE paper came out of Hopkins Biostats. Biostatistics work will be motivated by biological/biomedical/public health problems. Look up past students dissertations to get an idea if you're interested, and compare Stats to Biostats departments

In the same vain, for graduate programs/departments not in the top echelon (which I would say are Hopkins, Harvard, Washington, Michigan and maybe UNC)... your advisor/mentor becomes much more important. Generally speaking, what makes those top departments so great is the large number of well known faculty doing important research, whereas smaller, lesser ranked departments may only have 1 or 2. I'd argue that a great advisor from a lesser ranked school will set you up with a better future than a mediocre advisor from a top department. When choosing a place that isn't at the top, look carefully at the faculty you would want to work with, look where their past students have ended up, see if you can get in contact with current students and ask questions! It's obvious, but if you want to go into academia, you want to have an advisor that has a track record of placing students in academia...

Think about the applicant pool of people who would be interested in this advanced degree though. The type of person who simply desires to attain a masters in biostatistics is likely to be the type of student who has an aptitude for quantitative reasoning to begin with. The number of admitted applicants with lower quality profiles may not be due to rejected applications, but largely in part that these applicants have no interest in applying to begin with. Student like yourself who apply with lower scores, probably consists of a relatively small group, and the desire for the MS degree is likely influenced by outside factors (life events, eye opening moments, etc.). Despite the sub-par academic record, I bet letters of rec and the personal statement play a much bigger role in these circumstances. I think in the case of unfunded masters admissions, it would be more telling to see the distribution of the applicant pool, or at least be presented upper and lower quantiles of GPA and GRE scores. I'd like to see the percentage of applicants accepted with a 2.9 GPA out of those that applied with similar GPAs and GRE scores, and further differentiate these students on some basis of subjective ranking/perception of their LORs and personal statements. Lastly, I'd like to see all the non-admission profiles for comparison.

I'll be honest, I'm surprised too. With that said, the bar is relatively low for a masters... you are paying for it yourself after all.

The biostat department there is pretty new. The MS degree was implemented within the past 5 years I believe, and the PhD program just in the past year. From what I've heard, it's pretty strong for a new program. Couple Duke's med school reputation with their Statistics reputation, then I can only assumed their MS biostats program would be a solid choice. Honestly, looking at your list of schools... an MS from any of them would probably be about equal for an industry job. All things equal, I'd suggest going to a program based on where you'd like to most easily be able to find a job near when you graduate. So if you want to make a life in North Carolina after finishing, go to Duke or UNC if you are accepted. However, if you want to do a PhD, it matters a bit more. From that list - UNC would be the strongest, then UC Berkeley, and then I'd say the rest are about equal, i.e. choosing between them should really come down to specific faculty within department, or at least more specific research focused areas.

Both should be about equal, especially for an MS. My advice would be to go to whichever will be the cheapest for you. Vandy waives 80% tuition, but I think UT has RAships for MS students up to $15k/year. I will point out, if you're interested in cancer research, then look into see if students at UT have opportunities to work with the biostat division at MD Anderson. If they do, then there are is arguably no better place you could go for cancer biostatistics research, especially if you're interested in cancer clinical trials.

MS standards are lower because you'll likely be funding yourself. I was accepted into some top MS programs with a lower GPA than you have and around a 163 GRE (I honestly don't remember what it was, but it was low-mid 160s). Your math grades count highly though, and I did have A's in all calc, linear algebra, and stat classes.

Current second year biostats student chiming in. Many (most?) biostat programs won't require a strict measure theory course. Casella & Berger would be a good bet if you wanted to jump start your statistical theory, although it'll probably be what you use through the first couple theory courses. I think my best advice for anyone getting ready to enter biostats PhD in particular is to 1)Brush up on and/or strengthen your linear algebra skills, 2) ditto with calculus 3) learn a bit of R if you don't know it.

I went from a B.S. in Biology to a Biostatistics PhD program, which I'm currently half-way through my second year in. I had not taken real analysis, but did have multivariable calc and linear algebra, and I was admitted to a few PhD programs (mostly mid-range schools), and a couple top 5 MS programs. Real Analysis seems to be a deal breaker for the top PhD programs, but not for MS. Actually, if you have the biology/chem background and the necessary math background, I've found it to be really helpful. Given that biostats is largely an applied field, it certainly helps to understand the medical biology and chemistry of what you're applying your work to. In my experience so far, I've found the math major students to have little to no advantage over me in the mathematical/theoretical aspects of statistics. There have been a few occasions where they knew some math tricks that I hadn't come across before and were a little quicker to understand some things, but it was nothing I wasn't able to learn and come to understand. After having taken 3 semesters of statistical theory (essentially the entirety of Casella & Berger and Bickel & Docksum), plus the theoretical aspects of the advanced regression and modeling, there isn't anything I feel I don't understand and couldn't explain equally as well as anyone else in my department. However, in my area of applied research, understanding a little more than the basics of microbiology, immunology, molecular pathways, etc. has proven very helpful to me. It helps with how I approach problems, seeing potential conflicting variables, understanding better ways to help my basic science collaborators design experiments, etc. However, keep in mind, I'm not at Harvard, Hopkins, or Washington. Biostat departments at those schools are more heavy on theory than mine is, and I can't say it would have been equally as easy for me to adapt. The disadvantages would have likely been a little more pronounced, although I still believe I would have made it through their programs just fine.

Grad I wasn't really involved with my undergrad. I never lived on campus, didn't go to events... I was just there for my degree. It's a decent state school, but not really known outside of my region in the country. My grad school is more known. It's not world renowned, but I'm much more a part of the school here.

Someone sticky to this to the top of the page. It's been a couple years since I went through the app process, but I enjoyed reading it as a current student and this would have been of great interest to read when I applied. Perhaps I'll write something(s) like this to document my experiences as well.

Other than those you mentioned... Both Florida and Florida State have PhD biostatistics programs. Florida State's is a track within the department of statistics though, whereas Florida's is in the college of public health like most biostat programs. South Carolina and the Medical University of South Carolina also both have biostat PhD programs that have been around for a while too. UGA offers a biostat PhD now I think; it's only a couple years old. LSU school of public health has a PhD biostatistics program, but I've never heard anything about it with regards to quality.