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Journal Club

The student-run Journal Club is currently run as a hybrid series. It convenes on two Wednesdays each month from 12:30 to 1:30 p.m. (i.e., right before the department seminar on that day). Boxed lunches are provided to in-person attendees who register in advance. The 2023–24 Journal Club organizer is Jiangmei (Ruby) Xiong.

All are welcome to participate! Third- and fourth-year students are required to present at least once per year. The topic isn’t restricted to research specialties—it can be on programming, academic resources, or anything else other students might find useful. First- and second-year students are encouraged to attend Journal Club, but are not required to do so. Students in their third year and beyond are asked to attend and support their peers when not leading a meeting; while it is understood that you may occasionally miss a session for personal or professional reasons, the expectation is that you will attend at least 75% of the year’s journal club meetings.


  • All attendees should read/review in advance the article, software package, and/or other background material provided by the speaker. Here is a good intro: How to Read the Statistical Methods Literature.
  • The speaker will lead a general discussion, occasionally accompanied by a short presentation of the material.
  • Speakers are to send their journal article, software package, research topic, etc., to the secretary no later than two weeks in advance, for sufficient time to disseminate the material to all students.
  • Speakers are required to invite at least one faculty member to attend their meeting and participate in the discussion.

Why Journal Club?

Journal Club is intended to broaden students’ statistical horizons, bring them up to date on topics in the field, keep them abreast of new developments, and foster informal discussions and interactions with colleagues. Students practice communication and presentation techniques, sharpen analytical and synthesis skills, and gain experience in leading discussions and meetings.

Moreover, reading statistical literature is an essential tool for learning from and communicating with statisticians after graduation. The graduate curriculum, which is devised to teach you how to learn and think critically about statistical methods, is merely a starting point for acquiring the discipline knowledge you will need in your career; it is not designed to impart everything you’ll ever need to know to succeed. Professionally successful statisticians read the literature and continue to grow after graduation. Doing so efficiently and effectively is a learned skill, so now is the time to build your habit of engaging with the literature.