James E. Gentle

Graduate Students

I am the temporary advisor for most of the students entering the Computational and Data Sciences CSI PhD program in either the Computational Statistics or Computational Finance track. I can help new students develop a preliminary list of anticipated coursework, and advise them on what courses to take during their first few semesters. After that, students should select a dissertation advisor and form a dissertation committee.

I can serve as dissertation advisor for a limited number of students at any given time. Any student I accept must

  • be committed, and willing to work hard,
  • be strong in mathematics,
  • have strong computing skills,
  • maintain high ethical standards.

    My students must be prepared for hard work. I do not believe in shortcuts; a student who wants to skimp on the normal procedures should seek a different advisor. My students are expected to know and to follow the rules and procedures set out in the University catalogue and supplemented by statements in the CDS Student Handbook. (There are professors who do not require that their students follow the University and Department requirements for the degree. Don't ask me who these professors are, but your fellow students also know who they are. If you're looking for this route, ask fellow students or recent graduates. In that case, do not ask me to serve on your committee.)

    I like to work with students who have good backgrounds in mathematics. Mathematics is still the language of science. I expect my students in statistics to take the math stat course sequence CSI 972 / STAT 972 -- CSI 973 / STAT 973 (and do well in it). For my students in computational finance, the course CSI 672 / STAT 652 is sufficient, although the sequence CSI 972 / STAT 972 -- CSI 973 / STAT 973 is preferred.

    My students must have strong computing skills. In particular, they must be proficient in use of common operating systems, in programming in Fortran or C / C++, and in general use of R (or perhaps Matlab or Mathematica). Fortran and R are the languages I use most often. I strongly encourage students to learn and use R. The usefulness of R is greatly enhanced by a multitude of "packages". A good site to learn about the various R packages is http://crantastic.org. I also think all statistics students should learn SAS if they don't already know it. Just because.

    I believe both written and oral communication skills are important, and I will help students develop such skills. I expect these skills to be moderately well developed by the students' last years, and I will not write dissertations for students. I require that my students attend at least one face-to-face session at the GMU Writing Center. This can be for review of a research paper, the dissertation proposal, or one or more chapters of the dissertaton. The sessions are about 45 minutes long and can be scheduled at the webpage above.

    I strongly prefer that my students use LaTeX (or plain TeX) for scientific writing. (OpenOffice Writer, Word, or WordPerfect is good for writing memos or letters, however.) Of course, with TeX you need a good text editor -- and one with a good spell-checker. Macro or shortcut keys also help. (Actually, a word processor like OpenOffice Writer can often be set up to do a pretty good job as a text editor.) On MS Windows machines, Crimson Editor is my current favorite editor. On Linux/Unix I still use emacs.

    Several of my students have been part-time. While it took me a while to get used to the idea of a student pursuing a PhD degree part-time, I now realize that it is a realistic possibility. The student's full-time work often suggests areas for PhD research.

    Students should begin to participate in the activities of the learned and professional associations in their fields. Many societies offer free membership for full-time students. Sometimes this membership is limited, for example, the only publications that come with the membership are the society's newsletter, but even in this case, all students should avail themselves of this opportunity. The Institute for Mathematical Statistics (IMS) offers free membership to full-time students, and the American Statistical Association (AMS) offers membership to all students seeking a degree in statistics at a nominal cost. SIAM (Society for Industrial and Applied Mathematics) offers free membership to full-time students at academic institutional members of SIAM (GMU is an academic member), and offers greatly discounted rates to students who are not full-time. Go to the respective web sites and search under "membership" or some similar keyword.

    Informal associations among students outside of the classroom are important; not only for learning by working on statistics problems together, but also for forming networks that can be useful throughout one's career. This, of course, is another obstacle that faces the part-time student. Some of the CSI courses require group projects, and that helps to get students together outside of the classroom. A few times a year, I have a party at my home for some current students, some local alumni, and professional statisticians or other scientists.

    Academic honor

    Each of my students must assume the responsibilities of an active participant in GMU's scholarly community in which everyone's academic work and behavior are held to the highest standards of honesty.

    Make sure that work that is supposed to be yours is indeed your own.

    With cut-and-paste capabilities on webpages, it is easy to plagiarize.
    Sometimes it is even accidental, because it results from legitimate note-taking; nevertheless, it is plagiarism and it is illegal.

    Although the likelihood of "getting caught" should not influence your ethical standards, you should be aware of the fact that web searches can often identify plagiarism, and that there is even specialized software to facilitate such searches. Whenever I encounter phrases in a student's work that seem to be inconsistent with the usual language that the student uses, I routinely search the web for documents containing those phrases.

    Some good guidelines regarding written material are here:
    http://ori.dhhs.gov/education/products/plagiarism/
    See especially the entry "26 Guidelines at a Glance".

    The Committee on Professional Ethics of the American Statistical Association has prepared Ethical Guidelines for Statistical Practice that go beyond just the writing of articles and reports.

    Self-Plagiarism

    The definition of ``plagiarism'' applies to the ``work of others'', so copying your own work does not fall within the scope of the crime of plagiarism. Generally, of course, you are free to copy what you've written. I do this all the time with class notes, for example. Whenever you reuse any material, except for relatively brief background or supporting material, you should reference your original source. In the case of my class notes that have not appeared in formal publications, I do not reference my earlier work.

    Representing a rehash or restatement of earlier work as original work is wrong. Such self-plagiarism becomes a breech of academic honor, for example, when a paper submitted for credit in one instance is subsequently submitted for credit in another instance.

    Collaborative work

    I believe students learn by working with other students; hence, I encourage discussions outside of class, even about homework assignments. No communication with others can be allowed for work on exams, however, either in class or out of class. The criterion for allowing collaborative work is the extent to which the purpose of the work is evaluation versus learning. The purpose of an exam is about half and half; at least 90% of the purpose of homework is learning.

    Students must be aware of the requirements of different instructors, who may impose different requirements for course work.

    For homework and general topics relating to my own courses, I encourage discussion with others, including other students. I encourage use of any reference sources. Sources should be acknowledged in any submitted material, of course.

    Past PhD Students

    I am very proud of my past students, both at Iowa State University and at George Mason University.