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Evaluating programs that are new


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I have two admissions offers from relatively new (<10yr old) departments at UC Santa Cruz and UC Irvine. For example, UC Irvine has little placement data, as they only currently have 4 PhD graduates.

 

What route would you all recommend taking in evaluating the strengths/weaknesses of such programs? Over the long term, what sort of factors influence the reputation such programs develop?

Edited by CauchyProcess
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To assess quality of the faculty, you could look at faculty awards, publications, and citations. This site gives good advice on how to do that:
http://www.math.poly.edu/reference/advice.phtml

 

Some other measures that may be of personal interest to you are: average time to completion, job placement, percent who enroll in a PhD that actually finish, and overall "feel" and fit in the department. The DGS should be able to give you data on the first few, and the last of these would be very subjective, so it is a good idea to arrange visits the departments if possible (on that note, it might be worthwhile to visit schools you're waitlisted at too).

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One other thing to consider is that working with a mentor to get a few publications in high-quality journals before graduation and/or landing a prestigious post-doc can sometimes help to overcome a school's reputation (or lack thereof). It won't guarantee you a faculty job at a very elite program, but it could land you at a well-respected flagship or private university, rather than just regional schools and small liberal arts colleges (nothing wrong with those but those tend to be teaching colleges, and some people prefer to be at institutions where greater emphasis is on research). So in that respect, I'd say that the mentor you work with is a little bit more important than the reputation of the program. So the choices for mentors and opportunities to publish are some things to think about when you are picking a program to attend.

Edited by Applied Math to Stat
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I agree with the other posters here. I would add that ranking and reputation tend to be hard to change over a short time period. You should expect that by the time you graduate at either of those programs, chances are their reputations will be similar to what they are now. And that is when it might matter in terms of getting hired. Then again I am a strong believer that if you prove yourself via strong publications, it won't hurt you much that you went to one of these schools rather than a top-5 program. I certainly hope that if a faculty search committee is comparing two applicants, and one has stronger publications but the other came from a higher-ranked department, they would pick the applicant with better publications. That applicant has proven that he or she can make real contributions to the field of statistics.

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Thanks for article, Applied Math to Stat! Their ideas on looking up NSF grants, citations, and the like seem to be quite useful, and I'm going to collect some data and see what I find.

 

 

I agree with the other posters here. I would add that ranking and reputation tend to be hard to change over a short time period. You should expect that by the time you graduate at either of those programs, chances are their reputations will be similar to what they are now. And that is when it might matter in terms of getting hired. Then again I am a strong believer that if you prove yourself via strong publications, it won't hurt you much that you went to one of these schools rather than a top-5 program. I certainly hope that if a faculty search committee is comparing two applicants, and one has stronger publications but the other came from a higher-ranked department, they would pick the applicant with better publications. That applicant has proven that he or she can make real contributions to the field of statistics.

 

It's clear to me that once a program has a ranking/reputation, it won't change very much if at all over time. What's not clear is how that is initially established once a department is first created. For example, UC Irvine's Statistics department was recently founded by faculty that went there from UC Davis. UC Davis has a fairly well-regarded program, does that mean that UC Irvine's program will also be fairly well-regarded over time? Or, will it start at the very bottom of the rankings, and slowly move up?

 

I would also hope that a committee would pick the applicant with stronger publications, but I am not so sure that in practice this would happen, given that academia is a fairly small world and knowing other people is very important. It's really hard to tell how it all works while being a mere undergraduate, so I'm inclined to not think about it too much now, but rather decide later on whether or not academia is a good fit for me, especially if I face an uphill road and have better options elsewhere.

Edited by CauchyProcess
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From what I know about UCSC, they are very Bayesian and have some strong faculty and alumni particularly in Bayesian nonparametrics. That's a hot area right now, so if that's your jam, Santa Cruz would be a no brainer. I don't know what it's like to be a student there but it certainly seems like it's an up-and-coming department.

 

(I don't know anything about Irvine.)

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