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Logo of the Statistical Computing and Visualisation Section, showing joy plot, bar chart and scripting interface for code.

Statistical Computing and Visualisation 

Computing and graphics are vital areas of statistical practice,  especially important for today's data-driven practices. This section supports SSA members with: 

      • The provision of a community interested in computer hardware, software, and programming systems applied to statistical problems. 
      • Developing the use and understanding of statistical graphics to foster best practices in research, education, media and the general public.
      • Activities to build community, develop broader understanding and inspire new ideas and research.
      • Encouraging and rewarding impactful computing and graphics contributions with state and national awards. 

The 2024 Venables Award for New Developers of Open Source Software is open for applications. More details are here. 

The section is pleased to announce that we will be offering tutorials on a regular basis. Round 2 of tutorials will be held Tuesday March 26, 2024, from 9-12:30, 1:30-5:00.. Each tutorial will be half-day, 3.5 hours with 30 min of breaks. The cost for each is $150/300/75 for members/non-members/students. Details are available at this page. You can register for the tutorials from the SSA Events link. You can suggest topics for future tutorials here.


Meet the committee

Position  Name  Affiliation  Expertise  Sector 
 Co-chair (Graphics)

 Di Cook


Monash University, VIC  R, interactive data visualisation, exploratory data analysis, high dimensions, bioinformatics, ecology, environment, sports, open source software  Academia
 Co-chair (Computing)

 Dean Marchiori


Independent consultant, NSW  R Industry
 Committee

 Petra Kuhnert


 CSIRO, Qld R, intersection of statistics and machine learning, risk-based decision-making, environmental problems
 Government
 

 Nick Tierney

Telethon Kids Institute, WA  R, applied statistics, data wrangling, visualisation Academia
 

Merry Hoang


Monash University Python, R, javascript, dashboards (PowerBI, Tableau), interactive data visualisation, visual storytelling, GIS and geospatial analysis, housing and rental affordability, energy
Academia
 

 Emily Wong


Victor Chang Cardiac Research Institute, NSW  R, bioinformatics, genomics, multi-dimensional data, effective presentation of complex data/statistical inference in science 
 Academia


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