Data Visualisation Competition in a Box: A Webinar by the Statistical Computing and Visualisation section

The Statistical Computing and Visualisation section of the Statistical Society of Australia proudly presents a webinar titled "Data Visualisation Competition in a Box"

Date: Friday, 18 September 2026

Time: 12:30 - 1:30 pm (AEST)

Online via Zoom: details provided upon registration

Abstract:

Since 2024, the ANU Statistical Support Network has run an annual Data Visualisation Competition inviting research students to submit a graph from their own research alongside a short written explanation of what it shows and why it matters. The format is simple, low-cost to run, and has proven a popular and effective way to get students thinking critically about how they communicate data — while giving statistical consulting units a fun, visible way to engage with the research community. In this webinar, Professor Alice Richardson (Lead, ANU Statistical Support Network) will share the "recipe" behind the competition: how it's structured, judged, and promoted, what's worked well (and what hasn't), and how other institutions or SSA branches could set up their own version. Whether you're part of a university consulting unit, a statistical society branch, or simply curious about running a low-effort, high impact outreach activity, this session will give you everything you need to take the competition and run with it.

Presenter Bios - Professor Alice Richardson, ANU

Alice Richardson is a biostatistician at the Australian National University, where she leads the Statistical Support Network (formerly Director of the Statistical Consulting Unit from 2019). She completed her PhD at ANU on robust methods of estimation for multilevel linear models, after studying at Victoria University of Wellington. She spent twenty years teaching statistics at the University of Canberra before joining ANU's National Centre for Epidemiology & Population Health as a biostatistician in 2016. Her research spans robust statistics, data mining methods, applications to large health datasets, and statistics education.