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I am applying to a PhD program in biostatistics, and my undergrad was in B.S. applied math and limited pure math background; only topology and some analysis.

My question, though, is how much pure math is required to be good at statistical research and genetics? For my PhD, I think it may be silly to pursue genetics AND statistics specialization AND pure math courses; I think that is too ambitious.

I am seeking general advice. My interests are in statistical genetics, mathematical modeling of cancer informatics, and data analytics.

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  • $\begingroup$ Thank you for asking this as a new question. Welcome to CV. Good luck in your endeavors. $\endgroup$ – gung Oct 7 '14 at 3:23
  • $\begingroup$ I deleted my old comment, sorry for confusion. I love this website. $\endgroup$ – sophie-germain Oct 7 '14 at 3:53
  • $\begingroup$ I know applied folks who's never heard of the Lebesgue integral, seem to get by fine. $\endgroup$ – Michael Oct 21 '14 at 21:10
  • $\begingroup$ thank you. I am interested in linear algebra and statistics because these are the tools ready for dynamical modeling. especially in biology. advice? $\endgroup$ – sophie-germain Oct 22 '14 at 0:56
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My biostat department only requires calculus + linear algebra course to get into the biostatistics masters program. All the math that we were required to know for the more theoretical courses was taught to us.

I took a few of the more theoretical courses from our sister statistics department (Advanced Inference series taught out of Van Der Vaart, probability theory course) and for those type of classes you will certainly need to brush up a bit on your basic analysis + topology (e.g. understanding measure theory, basic set theory, compact sets, limit points, etc).

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  • $\begingroup$ yes I saw some textbooks on "Probabilistic Topology" in our library, so I know that analysis and topology is very important for being great at theoretical statistics. $\endgroup$ – sophie-germain Oct 7 '14 at 3:54
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    $\begingroup$ I read a paper by Dr. Frank Harrell who said that "a disadvantage to biostatisticians is that they have a tendency to be viewed as mere technicians". but I think that even if you studied pure math, one would have a risk of being considered "too esoteric" in one's specialty, in either case, there is a disadvantage. I only cite this because at my department, there seems to be an atmosphere where "Pure math" students are superior than applied. Thoughts? $\endgroup$ – sophie-germain Oct 7 '14 at 3:58
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    $\begingroup$ I would say biostatisticians are certainly not technicians. Although the problems we tackle are inspired by real data, that does not mean they are any less challenging theoretically. $\endgroup$ – bdeonovic Oct 7 '14 at 4:46
  • $\begingroup$ Can biostatistics applied problems motivate general probability theory? Or does biostats limit only to the applied field of biological data analytics ? $\endgroup$ – sophie-germain Oct 28 '14 at 20:20

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