How to Get Into a Biostatistics PhD Program

[math_n_stat]

Hi all,

I'm opening up this thread for those who, like me, didn't get into a biostatistics PhD program and are wondering what to focus on between now and next cycle to increase the likelihood of getting accepted. Obviously, we know that factors like undergraduate GPA, GRE scores, research experience, etc. are considered when an applicant's application is reviewed, but maybe some of us are unsure of which to prioritize. 

For me, I have a masters degree in clinical psychology with a concentration in research methods / statistics (statistical coursework from probability and statistical inference to multilevel modeling). Over the past year and a half, I have been completing mathematics prerequisites that were required by biostatistics PhD programs, but I think having Calculus III and Linear Algebra PENDING at the time of application played a significant role in this being an unsuccessful application cycle for me. Note: by May 2019 I will have finished through Linear Algebra and anticipate a 3.95 GPA in my math prereqs. 

I was offered admission to the MS in biostatistics at Columbia and MA in biostatistics at Boston University. I am wondering: Is it going to be impossible to get into a biostatistics PhD program without a biostatistics masters degree? I have an exceptional amount of research experience and publications, so it seems that I have three options:

1) Bite the bullet and get a second masters degree (most if not all credits will transfer to a PhD program and I might be able to get my current job to pay for some of this MS degree)

2) Save A LOT of money by foregoing the biostats MS and just get higher GRE scores (I had 157 in both V and Q)

3) Continue taking math coursework to demonstrate math ability (maybe completing coursework just through Linear Algebra is not impressive enough)

Would so greatly appreciate any advice (option 1, 2, 3, or some combination of them?). 

[Geococcyx]

I'm a current applicant, so don't take my opinions to heart.  That said, I don't think it would be terribly difficult to increase your GRE scores substantially, and that would already be very helpful to you -- I'm not sure that many PhD programs would take someone with a sub-160 Q GRE score seriously. 

Continued math would obviously help too.  I'm a bit confused as to where you are in terms of math content, since you seem to suggest you learned probability and statistical inference before calc 3, which seems counterintuitive if not inherently impossible. That said, if you can take real analysis and do well, that would be good.  If you have to take a sequences and series class first, then that won't help as much, but it still helps.  Any other proofs-based classes would be helpful as well, provided you can perform well in them.  

I feel like you could take a couple theoretical math classes, work on your GRE studying, and reapply next year without having blown a lot of money on an unnecessary master's degree.  I'm assuming these master's programs are 2 years, as well, and most PhD programs I've seen seem to only shorten by 1 year for those with an incoming master's, so I don't even think that a master's would help you finish your PhD faster in this case.  Best of luck, and I hope this has been solid advice.

[math_n_stat]

9 hours ago, Geococcyx said:

I'm a current applicant, so don't take my opinions to heart.  That said, I don't think it would be terribly difficult to increase your GRE scores substantially, and that would already be very helpful to you -- I'm not sure that many PhD programs would take someone with a sub-160 Q GRE score seriously. 

Continued math would obviously help too.  I'm a bit confused as to where you are in terms of math content, since you seem to suggest you learned probability and statistical inference before calc 3, which seems counterintuitive if not inherently impossible. That said, if you can take real analysis and do well, that would be good.  If you have to take a sequences and series class first, then that won't help as much, but it still helps.  Any other proofs-based classes would be helpful as well, provided you can perform well in them.  

I feel like you could take a couple theoretical math classes, work on your GRE studying, and reapply next year without having blown a lot of money on an unnecessary master's degree.  I'm assuming these master's programs are 2 years, as well, and most PhD programs I've seen seem to only shorten by 1 year for those with an incoming master's, so I don't even think that a master's would help you finish your PhD faster in this case.  Best of luck, and I hope this has been solid advice.

Thanks for the feedback! Do you yourself have a masters level degree in biostatistics? I interviewed for NYU's biostatistics PhD program this cycle and every other candidate there had a MS in biostatistics, statistics, or applied math. That says something about the candidates they are looking for.

Yes, I'm least worried about improving on the GRE. I thought my publications and research experience would make the 157s less of an issue, but I am now convinced that top programs are going to want to see scores in the 160s. 

Your confusion about my math background is warranted, haha. I DID take statistics courses with basically no math foundation! I took the statistics courses at Teachers College - Columbia University in their Measurement and Evaluation department, so perhaps I got away with this because they aren't a pure statistics department. I did very well despite the lack of math background, however, I know similar statistical courses in a biostatistics program will be more mathematically rigorous. Now, I have taken Algebra & Trigonometry, Calculus I and II, and am currently enrolled in Calculus III and Linear Algebra. These are the minimum requirements to apply to biostatistics PhD programs it seems.

Taking the math classes has been fine and even enjoyable, but it's not what I ultimately want to do and I am eager to be taking biostatistics courses. I wish I knew how important real analysis will even be as a biostatistician (how much will I use it?). If Columbia is letting me into their biostatistics MS (which consists of the same classes a PhD student of theirs would take!!) without this course, that suggests to me that real analysis is not completely necessary (but I could be wrong!). 

[Geococcyx]

I've been applying directly out of undergrad -- for what it's worth, I didn't sense that the places I visited were taking mainly master's students, so that may just be an NYU preference.  Regarding real analysis, I'm guessing you're going to need it for any sorts of methods development, although I've been given to understand that generally you won't be using a lot of the measure theory you learn (if you learn it -- most biostatistics departments don't really seem to emphasize measure theory, UNC and Washington excepted).  I know some people do go into PhD programs without real analysis, though -- I recall someone getting into NCSU stat without real analysis a couple of years ago, and someone I met at Illinois stat's visit day said they didn't take real analysis before coming there either.  If you don't take it, then you're still gonna have to cover some of it, and you'll probably be playing catch-up, so I would think it would be to your benefit to go ahead and learn real analysis if you can.  

Again, I haven't even taken a grad school class yet, it would be to your advantage to get opinions from the older people on here, or perhaps some Columbia statistics professors if you know any of them.  

[omicrontrabb]

I'm applying to biostatistics PhD this cycle and have been to several visit days. Very few of the accepted students I met had masters degrees. However, almost all of the students had bachelor's degrees in statistics, math or applied math.

You mentioned that the statistics classes that you took at Columbia were for teachers and did not require much math as a prerequisite. I'm going to guess they were pretty applied courses and admissions committees don't seem to value those very much.

For comparison, my stats classes in undergrad had Calc 3 and Linear Algebra as prerequisites.

If you're currently enrolled in Calc 3 and Linear Algebra, there is no way you'll be admitted to biostatistics PhD programs. Every accepted student, plus tons of rejected ones, will have aced Calc 1 and 2. Having good grades in those is not enough to show admissions committees that you will succeed in mathematically rigorous statistics courses.

I think having A's in linear algebra and calc 3 would make a difference. The math classes are prerequisites, but also a primary way of showing you are capable of succeeding in mathematically dense courses. If I were you, I would not go to a masters program and instead enroll in real analysis and a mathematical statistics course and also work on improving your quantitative GRE score. Then you should have a shot at biostatistics PhD programs at schools like VCU. 

I will add one more note, I'm assuming you're a domestic student. If you're international, it would be difficult to get into a biostatistics PhD program regardless of what you do, because the competition is very fierce.

 

[math_n_stat]

2 hours ago, omicrontrabb said:

I'm applying to biostatistics PhD this cycle and have been to several visit days. Very few of the accepted students I met had masters degrees. However, almost all of the students had bachelor's degrees in statistics, math or applied math.

You mentioned that the statistics classes that you took at Columbia were for teachers and did not require much math as a prerequisite. I'm going to guess they were pretty applied courses and admissions committees don't seem to value those very much.

For comparison, my stats classes in undergrad had Calc 3 and Linear Algebra as prerequisites.

If you're currently enrolled in Calc 3 and Linear Algebra, there is no way you'll be admitted to biostatistics PhD programs. Every accepted student, plus tons of rejected ones, will have aced Calc 1 and 2. Having good grades in those is not enough to show admissions committees that you will succeed in mathematically rigorous statistics courses.

I think having A's in linear algebra and calc 3 would make a difference. The math classes are prerequisites, but also a primary way of showing you are capable of succeeding in mathematically dense courses. If I were you, I would not go to a masters program and instead enroll in real analysis and a mathematical statistics course and also work on improving your quantitative GRE score. Then you should have a shot at biostatistics PhD programs at schools like VCU. 

I will add one more note, I'm assuming you're a domestic student. If you're international, it would be difficult to get into a biostatistics PhD program regardless of what you do, because the competition is very fierce.

 

This is great feedback. 

The statistics courses weren't for teachers, it was just at Teachers College at Columbia. The title of that particular school makes it sound like a school for students who want to become teachers, but that is not the case - I had my statistics courses with people getting MAs in Applied Statistics. So, that part you are right about - it was mostly application, extremely little theory. 

I am glad you and @Geococcyx seem to be on a similar page about the value of a real analysis course. That makes me feel much better actually. I would rather finish this semester (Calc III and Linear Algebra, both of which I anticipate getting As in) and then take real analysis and improve my GRE scores rather than pay a lot for a MS. I also have two pending publications, so if those work out I will have a total of 5 publications (first author on one) by next application cycle.

I hope the updated coursework, improved GREs, and additional publications will be enough for them to accept my clinical psych and applied stat background!