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Some Modest Advice for Graduate Students


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It is good advice for the most part. I think a good goal for most PhD students who are aiming for academia is two first-author papers completed and one project that is still "in the works." If you plan to go into industry, then the publications aren't going to be as crucial, but in that case, I still think at least one first-author project fully completed is a good target (you may not have much say in this matter anyway -- usually, the PhD advisor will stipulate their own requirements to sign off on a student's graduation, and for many, that is going to be two finished projects).

I think many PhD students should understand that with a few exceptions (e.g. medical crises, family emergencies, or other extenuating circumstances), the amount of time to completion IS actually very much in their control (that is, completing within 5 years vs. taking longer). I have seen some students take 7-9 years to finish the Statistics PhD, but I don't think they really needed to languish that long if they had been more proactive and done *more* than what their PhD advisor requested of them from the get-go (i.e. read papers on their own, try different methods on their own and then discuss these with their advisor). If all you do is what your PhD advisor asks you to do and if you never ask questions because you're afraid of "looking dumb," then don't be surprised if it takes longer to finish. The PhD advisor is there to GUIDE you and can point you to certain papers to read or certain new things to try, but ultimately, it is YOUR work that you must own and be proactive about.

Edited by Applied Math to Stat
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  • 3 weeks later...

A few other things to keep in mind: when you're still taking courses, it can be easy to get discouraged if there are other students who seem to be "faster" or more clever when it comes to taking tests. Specifically in the field of statistics, it can be daunting for some domestic students, because the international students have (in general) been exposed to more mathematics. However, it is important to do your best and not to focus much on other people -- what's most important that YOU understand what's going on in your classes. 

Moreover, acing classes and exams is *not* what earning the PhD is about. Once you get to the research phase, most people will be on even footing at that point -- since just about everyone needs to teach themselves a brand new area. And there are quite a few students who were acing all their classes but who struggle through research, because they had difficulty adjusting from the mindset of student to researcher (the latter of which is requires a completely different mindset from being a top student: the latter is necessarily about making mistakes, muddling through things that don't seem to make any sense at first, being stuck for WEEKS at a time, abandoning unpromising avenues, etc.).

Even if you succeed at completing your PhD, it can still be intimidating because there are established researchers who seem to be churning out papers nonstop in top journals, etc. But just keep in mind that these are people who have been doing what they have been doing for many years, *and* despite all of it, even they still get a lot of their papers rejected. Plus, it can take years to reach their level of skill and expertise. But if you keep pushing yourself, you can eventually build your skills and become like them (if you aspire to that) with more experience. 

Edited by Applied Math to Stat
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On 3/26/2018 at 8:14 AM, Applied Math to Stat said:

It is good advice for the most part. I think a good goal for most PhD students who are aiming for academia is two first-author papers completed and one project that is still "in the works."

Thanks for the advice.

How would you suggest students start writing publishable papers in their programs? Stearns, the author of the first article, recommends being a co-author on a professor's project and publishing your thesis as a series of manuscripts. Do you feel that these are viable options in the field of statistics? If not, what are some other ways to start writing?

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13 minutes ago, Zaphod2020 said:

Thanks for the advice.

How would you suggest students start writing publishable papers in their programs? Stearns, the author of the first article, recommends being a co-author on a professor's project and publishing your thesis as a series of manuscripts. Do you feel that these are viable options in the field of statistics? If not, what are some other ways to start writing?

In statistics (and I think biostatistics too), the PhD thesis is usually two or three of your papers stapled together, along with a literature review and a conclusion/future work section. Your PhD advisor will help guide you along the way, so you won't be left completely to yourself -- they will help you find a "doable" open problem for your first project, and help you through the entire process of: manuscript preparation (you'll probably go through multiple edits *before* even submitting to a journal), the initial submission, revise and resubmit process, the point-by-point response to reviewers, etc. Your advisor will know what is considered publishable quality and also have some idea of which journals are the most appropriate venues to submit your work to. 

Most PhD students have no idea what open problems are out there when they first start, so the bulk of the first semester after passing written qualifying exams will probably be spent just reading papers and books, teaching yourself a new area, and doing small exploratory projects (e.g. running simulations, reproducing results from a "seminal" paper, or something like that). A lot of stat/biostat PhD students will also have one or a couple of third/fourth author publications from helping out other people on projects (i.e. they'll be listed as a co-author for writing some R code, performing some data analysis, or otherwise making some small contribution).

However, by the time you finish, you should ideally have at least two FIRST author papers where most of the work was your own (the idea, the algorithm(s), the theory and proofs if any). At the end of the PhD, you ideally *should* know more about your topic than your advisor (it's your research after all).

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