(Note: This is my second installment on grad school, you can read the first part on coursework, the difference between a Master’s and a Ph.D., and proving your worth, here.)
Advancement to candidacy
After finishing coursework, the next step in our PhD program is to “advance to candidacy.” This is the formal process of proposing your dissertation research. Our department has a diverse set of research interests, both theoretical and applied, so dissertations can take a variety of forms. This is yet another difference between Master’s and PhD projects– typically, Master’s projects are more directed by faculty members and PhD projects are chosen primarily by the students themselves. Either way, the process begins with a conversation between the student and his/her advisor.
Before an in-person proposal of the project, the candidate prepares a written report outlining their research plan (called a “prospectus”) that is sent out to a committee of faculty members chosen by the student. This committee is led by a departmental professor, or “chair” who helps guide your project plus three other professors who will evaluate the quality of your project and provide guidance during the process. Of these three professors, one must be outside the statistics department. (One of the bigger challenges in forming any dissertation committee is that for faculty members to serve, they must be full, tenured professors in the department and it’s important to note that not all professors teaching for a department have attained this status.)
In my case, my doctoral committee is relatively large. My advisor is Mark Hansen, and my two departmental members are Mark Handcock and Song Chun Zhu. Then, because my work is quite computational, I’ve added two computer scientists: Todd Millstein and Alan Kay. Because I’m focused on statistics education I also included Rob Gould.
Once you’ve officially created your committee and written the prospectus, you have a formal presentation of your dissertation proposal. This usually means creating a Beamer presentation, dressing up in a suit or other formal wear, and sweating your way through an anxious presentation to be followed by a set of questions from your committee. The committee then deliberates in private, discussing your presentation and perusing your academic record. Following this deliberation they inform you of whether you have passed (AKA “advanced to candidacy”) or not. Note that in practice, everyone passes the proposal since your advisor wouldn’t allow you to move forward in presenting your proposal unless you were considered ready to pass.
Students typically advance to candidacy at the end of their second year of study or perhaps at the beginning of their third. I’ve completed a late proposal (after my third year) but since I’m now on track to finish in 2015, I do feel as though I’ve caught back up. In many PhD programs, once you’ve advanced to candidacy the department awards you a Master’s degree – and if you’d like you could decide to leave with that degree alone, keeping in mind that you originally had your sights on the PhD. However, as of last year the UCLA statistics department has stopped this practice, perhaps because of the increasing popularity of the Master’s degree as its own program and the desire to prevent PhD students from ‘dropping out’ along the way with a Master’s. Instead, students who achieve candidacy recieve a certificate declaring the student as a “C. Phil,” or Candidate of Philosophy.
I found this C. Phil process to be surprisingly motivating, since in order to get a Master’s degree I would still have to write a Master’s thesis. Facing a massive, complex writing project in either case, it seems like it wouldn’t be much more work to get the PhD.
Writing and defending
Once you have advanced to candidacy you can begin to work on your project with your committee’s blessing. At this point (where I currently am) you ‘just’ need to finish your dissertation. This requires lots of thinking, writing, consulting with committee members, and thinking again. It’s truly the hard work of the PhD, since there are few external deadlines given to you and it’s now up to you alone to both finish the research and write up your findings.
Eventually, you will defend this line of research in the formal “dissertation defense,” when your committee will evaluate your project and decide whether your work is acceptable or whether you will need to complete more work to graduate. Again, this is hopefully a formality since your advisor will let you know if you are ready to defend or not. While you may emerge from the defense with many required revisions, you should never completely “fail.” (At least that’s what I tell myself!)
The fun stuff
Of course, all work and no play makes graduate school a hellish ordeal! So, one of the best things about the UCLA statistics department is that we always try to have fun. Many times when visitors have come to the department they’ve remarked about how social and ‘normal’ we all are– not at all like the stereotypical Stats Nerd. It’s hard to say whether that stereotype actually exists, but I can certainly say with confidence that we have built a great community.
For example, at least once a year a grad student designs a new departmental t-shirt, which we all wear with pride.
We also have a yearly tradition of competing against other science graduate students in a keg race. Typically, the Physics department is able to finish their keg first, but this year the joint statistics and math team was victorious!
Beyond these more formal events, we are often found hanging out together. Until this year, the graduate student offices were arranged to open into the same lounge area, where people would gather informally almost every day. We’ve just had a big change in the office situation, but I’m sure we’ll still find a way to be social. Nearly every week you can find students going to happy hour or on a hike.
Finally the alumni of the department stay in touch and are quite friendly. Our alumni list includes familiar names in statistics like Nathan Yau of FlowingData, Jake Porway of DataKind, and Roger Peng of Simply Statistics, as well as graduates pursuing tenure-track professorships, like Mine Çetinkaya-Rundel at Duke and Andrew Bray at Mount Holyoke.
Do you have more questions about statistics graduate school? Ask me in the comments!