IASE 2023 Satellite Conference
Fostering Learning of Statistics and Data Science
July 11–13, 2023 | Toronto, Canada | In person and online

Visit the conference website for details and to register

Conference Overview
• Satellite conference happening July 11–13, 2023, just before 64th World Statistics Congress
• Co-organized by the International Association for Statistical Education (IASE) and the International Association for Statistical Computing (IASC)
• Presented with the support and sponsorship of the International Statistical Institute (ISI), the Department of Statistical Sciences at the University of Toronto, and the Canadian Statistical Sciences Institute (CANSSI)
• Hybrid format (participate in person in Toronto, Canada, or online)
• Theme: Fostering Learning of Statistics and Data Science
• 40+ presentations,
• 35 posters

Keynote Speakers
• Chris Wild (University of Auckland, New Zealand)
• Shingai Manjengwa (Vector Institute for Artificial Intelligence, Toronto)
• Jürgen Symanzik (Utah State University)

About the Theme
The broad theme of the conference is "Fostering Learning of Statistics and Data Science". The data landscape is constantly shifting, driven by perpetual technological, economic, and societal developments. Information is now recorded and shared at unprecedented rates, with statisticians and data scientists called to make sense and use of increasingly complex data. Conventional methods of data analysis are being adapted for this new landscape, while additional approaches are being developed under the umbrella of Data Science. Naturally, these changes have profound implications for education too, raising important questions about what, when, to whom, and how we teach Statistics and Data Science. The theme aims to engage with these questions in order to promote and sustain learning in our field.

We invite you to participate in this Satellite Conference, to join us in sharing knowledge, questions, and ideas that enable us to learn from the work of colleagues from around the world and help to advance the teaching and learning of Statistics and Data Science.