hedgie

I defer to cyberwulf. He knows way more about it than I do. Or anyone else. I think if you read through threads you'll get a good idea. Also apply to a decent amount of programs because if funding issues....especially state schools.

Yeah, maybe but the 3-4 were 250+ for phd's only. But I agree with the rest of your beliefs for the most part it was mixed ms/phd's. they were mostly foreign apps though. Maybe 60-75%.

Cyberwulf...........very true but the OP is in an applied stats program. I have seen some theoretical programs deal with large data sets still so it depends on the school but that's a good point though re: application in seeing messy real world data. In regards to your second question...yet I applied to 4 of them and they have 250-350 apps unless they blatantly lied...although I don't think so...many are foreign apps though.

I am interested in bio as well. But the advice I always heard was to do plain stats because it was more versatile and you can get all the Biostat jobs. I have heard some decent counter arguments to this as well, but others can chime in as I think that was always the general consensus. Although I think bio programs in general are easier to get into with a strong math background. Someone correct me if I'm wrong. You need to apply lower though for sure. Even the top 40-50 stats schools are getting 300+ apps a year now.

You can always apply but why not pick lower schools as cyberwulf suggested. Emory? Are you set on bio? You can always do stats or applied stats and work in bio? Why not just move up and do the Phd in applied stats at the univ your at? Then Goto bio for a job via a postdo

All the top schools you are interested in.....your profiel looks really good. Just apply to 5-10 institutions with some safeties because funding is hard. Are you a US Citizen? You can retake the GRE Q if you want...isn't out of 170? 165 should be 'OK' given the rest of your profile.

Pre-req's for a MS in Biostats you need at least single variable, multivariable calculus, and linear algebra. This usually takes 3 semesters. I am not as familiar with bio programs but the sciences are less important to take as an undergrad, though educationally they are helpful. To continue for a phd many programs (most) require the undergrad sequence in real analysis. Take as much linear algebra and real analysis as you can. You need to score high on the gre quant section in particular 750+. A PhD or MS in statistics can do what a PhD in Biostats does but the other way is more difficult. Of your options taking the pre-req's in fall,spring, and summer seems possible and I would apply to Suny's MS in statistics program. But that is just my opinion others with more knowledge in Biostats may be more helpful. An intro to programming course would be helpful too.

Thanks Poisson!

Thanks so much cyberwulf and Poisson! When you say numerical was easy to pickup on your own do you just mean a intro to numerical analysis or would the numerical linear algebra be similar and easy to study on my own? I wish we had a measure theory course offered but alas my school does not and I can it step into the real analysis 2 grad course...so I'll have to wait until next year.

What exactly do you mean by "mathematical culture" courses? I assume these will only be helpful in certain areas of stats that I do not know if I will go into or not. I know Stochastic is good for time series but who knows what I'll do. I guess my best option is wait till grad school and take them if I need them or read the books and learn it myself. Thanks for any comments thoughts and your initial response!

I am looking to do a PhD in Stats. I have limited time in the spring but could take a one or both: a stochastic processes course, and numerical linear algebra. Any advice whether these would be of value, or could one just self study the stochastic?

I know the Math GPA's are important for MS Stats and PhD programs but do CS course grades matter much? Obviously C's are bad but if you take a few and make B's but have a 3.7 in your math's does it matter? Thanks for any input. Best of luck to the OP.

How crucial/important is a school's ranking and the schools ability to place Stats PhD's in good jobs (outside of academia)? Is it more based on regional connections of prof's, industry connections or does one need to be in a top 30 program? As well any rec's for schools in the southeast and north east that are a mix of applied and theoretical?

Quick question regarding the Master's.....and this is more my situation. I did poorly in undergrad, returned to finish a Math Bachelor's and may do a Master's before a PhD. Will adcom's really even be paying much attention to the UG work or will it be my Master's work that would be focused on? I wish I was your age and was taking my do-over fallen....don't give up you have plenty of time/opportunities!

Thank you! I had planned on doing Real Analysis I/II as my electives in addition to the electives I listed out if I did the MS in Stats. Do you think I'd be better served if I could go to the program, not too far away which has measure theory in a sequenced grad course combined with RA versus the MS in Stats with electives in Real Analysis I/II? So it'd probably be a Math MS with the opportunity to get into their Stats PhD program which is unranked, but the placements of their grads has been good, and I am unsure of their research areas yet relative to my interests. I do have a couple of other follow up questions if you have the time to answer them. In finishing my undergrad work would abstract algebra, and partial differential equations be more useful than CS courses. I had been under the impression the adcom's look favorably on the Math's (as you also pointed out) and that CS beyond an intro to programming course was in about all that is necessary for the Stats PhD, the other languages one would learn on their own. Originally I had thought of not taking PDE's and abstract algebra (as well as one other math course) and getting a minor in CS, which would get me to a data and algorithm's course, and some C++, but I do not know how helpful that would be or not for the Stats PhD. Is it correct to think I would be better off with the math? Thanks for your time and advice, and thanks in advance.