Jump to content

bayessays

Members
  • Content Count

    355
  • Joined

  • Last visited

  • Days Won

    2

bayessays last won the day on August 12 2018

bayessays had the most liked content!

About bayessays

Profile Information

  • Application Season
    2013 Fall

Recent Profile Visitors

3,423 profile views
  1. I don't have any inside insight into the department. Have you seen any professors there who match your research interest? I wouldn't put too much stock in coursework - the research is what matters in the end.
  2. If you're going to a statistics program, you're probably good. If you're going biostat and need to use SAS, it might be a pain. I would stick with your Linux and deal with any unlikely problem if it comes up - unless you're going to a biostatistics program that forces you to use SAS and doesn't let you remotely access it, you won't encounter anything that will make you buy a new computer.
  3. They're all amazing schools, so bring your decision down to research fit and location. If you want to do Bayesian stuff, obviously go to Duke. If you're interested in ML, UW has some great ML people (Emily Fox and Witten) as does Berkeley (Jordan). I'd visit and follow your gut. You can't go wrong. If you are choosing between programs that are current ranked 12 and above on US News (Stanford, Berkeley, Washington, Harvard, Chicago, Duke, CMU, Michigan, UPenn), I don't think there is a one size fits all answer.
  4. I know people who are super happy with both. Think that you're going to be using R, maybe ssh'ing into a computing cluster at some point, writing LaTeX, maybe programming in Python or C depending on your research. In which environment would you personally feel most comfortable doing these things? Since RAM is cheap, I would recommend getting the highest RAM possible to run R since it is memory intensive with big data sets.
  5. I think academic placements are not always the best barometer sometimes because of selection bias. Someone who chose UCLA over TAMU probably puts higher value on living in California or a big city or good weather and might not be willing to go wherever for a professor job - especially in California, many people decide they would rather just not move and decide to go into industry or get whatever nearby job they can find. UCLA is a great department, but from my (limited! biased! I could be totally wrong) perspective, I think of them as having less big names than the other two. Penn State has Murali Haran - if you're interested in MCMC stuff, I'd say go there. Is location important to you? TAMU has a couple good profs I can think of that have good placements, but if you don't want to work with them, are you willing to live five years in College Station over LA?
  6. bayessays

    Fall 2019 Statistics Applicant Thread

    In my experience, one exception is Ohio State, which in two separate years offered me admission in April after I had already accepted other offers.
  7. Stat PhD now Postdoc's assessment is dead on. Ohio State is a good department, but the ceiling is higher if you get through chance to work with those top people at UW. You will definitely not only do applied work there, especially if you actually want to do more theoretical work - there is plenty of opportunity.
  8. It is somewhat harder to go from biostatistics to statistics than the other way around, but not impossible. Part of it is a selection problem - students in biostatistics generally do somewhat less theoretical research and enjoy the biostatistics environment. Another issue is the faculty. There might only be one or two professors in a biostatistics department doing the type of research that gets you a statistics job - publishing in JASA, not JAMA, is what matters for top tenure track statistics jobs. If you go to Berkeley biostat and work with Van der Laan, you'll be in good shape, but if you want a job in a statistics department, you should probably go to a statistics department. If you go to a non-top 5 biostat school, you're likely going to end up at a biostatistics school ranked lower than yours. A Columbia biostat PhD has virtually no chance at becoming a professor at a top 40 statistics department, unless you somehow got super lucky and managed to form a relationship with one of their top statistics professors and then published with them. It's hard to bet on forming such a relationship - often the statistics and biostatistics departments at schools have almost no interaction. Do not get a computational math PhD if you want to be a statistician. You are limiting your future marketing of yourself to a much smaller niche. I would also suggest getting a PhD in statistics, not biostatistics, unless you actually want to be a biostatistician, but that matters much less.
  9. UIUC is a well respected department. As for industry jobs, what industry are we talking about? The advantage to NCSU is getting jobs in the Triangle area. If you want a tech job in California or NY, you're in good shape from either school. Unless you definitely want to work in NC triangle, I think your decision should come down to research interests, location preference, and department size (NCSU is huge, UIUC much smaller).
  10. bayessays

    Texas Stats PhD Programs

    In response to Bayesian1701, Austin is expensive relative to College Station, but the student areas of town are really not that expensive. You can live on their stipend. If it would calm your nerves a little, UT has at least one professor who publishes a lot and is 100% frequentist. If you're open-minded to the idea of Bayesian statistics, it probably won't be a big deal. Two other things to consider are size and coursework. TAMU will have more students which has pros and cons. I believe TAMU also has a more traditional course sequence which will include some pretty rigorous courses in theoretical statistics and measure theoretic probability, while UT has a more Bayesian oriented curriculum.
  11. bayessays

    Laptops for Ph.D. programs

    I'm not super familiar with this exact problem - is it specific to Macs? I've had issues with RStudio on other operating systems, too, mostly related to crashing with memory overloads. Another was some package compatibility issue with Linux. I don't think there's any reason to believe RStudio would work better on Windows. I know people who have used all 3 major operating systems without issue, so my advice would be to use the one you're most comfortable with. If you go to a biostatistics department that uses SAS, though, you might have some hassles if you use Linux where it's not available.
  12. bayessays

    Laptops for Ph.D. programs

    Is there a reason you're switching from Mac? I think they're the best of both worlds for a statistics grad student. Depending on your research and how much programming you do, having a Unix computer would probably be easier for most people than Windows. Other than that, yes, I'd make sure to have a lot of RAM because I've always had issues with RStudio crashing.
  13. bayessays

    Texas Stats PhD Programs

    No, he was a student of James Scott, one of the statistics professors. The department is new but the statisticians are not. UT has at least 4 elite, renowned Bayesians. If you work with them, it does not matter that the department is new. Out of their 4 PhD grads, 1 has gone into industry, and the other three were post-docs at Berkeley statistics, Princeton CS and UChicago biostatistics.
  14. bayessays

    Texas Stats PhD Programs

    Yes there is a nice variety there. I looked a little more at Rice. Schweinberger publishes a lot in top journals, but most their other professors publishing in top journals are very young - they don't have the big names UT has. My decision process, personally, would be like this: 1) Do you want to be a Bayesian? If so, go to UT, no question. If you definitely don't, don't go to UT. 2) if you don't care about the Bayesian thing either way, take a look at your political beliefs and preference for surrounding area. I think environment is huge when you're making a decision on where to spend 5 years. If you're a liberal hippie, go to Austin. If you're more conservative or like small towns, you might enjoy College Station. Houston is more moderate and a normal big city. 3) Weigh the above factors with career goals. If you want to be a data scientist, go where you'll enjoy it the most, and look at the professor research interests. If you want to be a professor at a top department, I think going to UT and working with one of their top 4 guys has the highest ceiling, but I've looked at Rice's placement and they've put multiple people in TT jobs at PhD granting places recently, including TAMU.
  15. bayessays

    Texas Stats PhD Programs

    Texas A&M, like Iowa State, is a very old and large program - they still turn out a decent number of grads who land good positions, but if you go there you will have to find one of the more well-known advisors and publish (as you would anywhere, of course). I suspect they are decreasing in the rankings because they have trouble recruiting top students and faculty to live in College Station, which should probably be your main factor in your decision. UT Austin has some of the biggest names in Bayesian stats, and if you go there and work hard with Scott or Carvalho or Walker as your advisor, you'll be in great shape for a good post doc - there first PhD grad got one with Michael Jordan at Berkeley. They've lost two faculty members including their department chair in the last couple years. I don't know a ton about Rice, but none of their faculty have stuck out to me and I don't often see their grads as professors, but that may be because of their size. I would say they're a step below the other two schools.
×

Important Information

By using this site, you agree to our Terms of Use and Privacy Policy.