Hello stressed out students :(

It’s been a while since our last newsletter, but we’re here to let you know of our course planning workshop and Cal Week events hosted by the Statistics Department!

Our semesterly course planning workshop is happening TODAY (6/26) at 6:00 PM PT. Come thru to learn about the more enrollment logistics from our advisors, advice from us, and ask any questions that you want us to have a shot at. Register at https://susa.berkeley.edu/fa21/course-planning to receive a Zoom link.

Then, we have our Cal Week events by the Statistics Department! Read about them here: bit.ly/StatsCalWeek or quickly glance through them below:

2021 Apr. 27: Studying Statistics at Cal

  • Time: 4:00 PM - 5:00 PM

  • What:
    This event is intended for INCOMING STUDENTS, but please feel free to pitch into the chat if you want to answer questions.
    Come to an information session on the Statistics undergraduate program! We will briefly review the major and minor requirements, and current students will talk about what it is like to study statistics at Cal.

  • Info: https://statistics.berkeley.edu/about/events/cal-week-event-studying-statistics-cal

2021 Apr. 27: A.I. in Practice - From Self-Driving Cars to Automated Scoring in SportsTime:

2021 Apr. 28: Neyman Seminar

  • Time: 4:00 PM - 5:00 PM

  • What: Consider the subgraph sampling model, where we observe a random subgraph of a given (possibly non random) large graph $G_n$, by choosing vertices of $G_n$ independently at random with probability $p_n$. In this setting, we study the question of estimating the number of copies $N(H,G_n)$ of a fixed motif/small graph (think of $H$ as edges, two stars, triangles) in the big graph $G_n$. We derive necessary and sufficient conditions for the consistency and the asymptotic normality of a natural Horvitz-Thompson (HT) type estimator. As it turns out, the asymptotic normality of the HT estimator exhibits an interesting fourth-moment phenomenon, which asserts that the HT estimator (appropriately centered and rescaled) converges in distribution to the standard normal whenever its fourth-moment converges to 3. We apply our results to several natural graph ensembles, such as sparse graphs with bounded degree, Erdős-Renyi random graphs, random regular graphs, and dense graphons. This talk is based on joint work with Bhaswar B. Bhattacharya and Sayan Das.

  • Info: https://statistics.berkeley.edu/about/events/neyman-seminar-41

2021 Apr. 29: Celebrating Statistician David Blackwell

  • Time: 5:00 PM - 6:00 PM

  • What: Peter Bickel, Department of Statistics, UC Berkeley (Panelist/Discussant) David Harold Blackwell (April 24, 1919 – July 8, 2010) was a Professor in the Department of Statistics at the University of California, Berkeley, who made seminal contributions to game theory, probability theory, information theory, and Bayesian statistics. He was the first African American inducted into the National Academy of Sciences, the first Black tenured faculty member at UC Berkeley, and...

  • Info: https://statistics.berkeley.edu/about/events/celebrating-statistician-david-blackwell