Event

Cutting Edge Lecture in Science: Did this make that happen? Causation, causality, and the statistician

Thursday, December 6, 2018 18:00to19:00
Redpath Museum Auditorium, 859 rue Sherbrooke Ouest, Montreal, QC, H3A 0C4, CA
Price: 
FREE with admission to Museum

By Erica Moodie (William Dawson Scholar & Associate Professor, Department of Epidemiology, Biostatistics, and Occupational Health, Faculty of Medicine, McGill). A significant proportion of research seeks to discover causes – causes of disease, of disparities, of longevity. Causation has been considered by philosophers, religious scholars, mathematicians, for millennia but only recently in ways that are amenable to study with the larger datasets that are available to researchers today. In the last several decades, statisticians have developed a framework to help guide data analyses that can help to understand whether observed relationships learned from data may be “real” or not. I will touch on some historical views of causation, and explain an approach that is used by statisticians to design valid analyses.

 

 

Land Acknowledgement

McGill University is on land which has long served as a site of meeting and exchange amongst Indigenous peoples, including the Haudenosaunee and Anishinabeg nations. We acknowledge and thank the diverse Indigenous peoples whose presence marks this territory on which peoples of the world now gather.


Rematriation, Repatriation and Restitution Statement

We acknowledge that the return and restitution of cultural and natural heritage to communities of origin is an essential part of reconciliation and of recognizing the fundamental rights of Indigenous Peoples. As part of wider efforts to activate the standards presented in the Canadian Museums Association Report Moved to Action: Activating UNDRIP in Canadian Museums (2022), the Redpath is working towards pro-active restitution practices. As per our Collections Management Policy (2024), repatriation requests will be received by the Redpath Museum Director and will be treated on a case-by-case basis.

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