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UID:20251129T143748EST-6375TwnAmK@132.216.98.100
DTSTAMP:20251129T193748Z
DESCRIPTION:By Erica Moodie (William Dawson Scholar & Associate Professor\,
  Department of Epidemiology\, Biostatistics\, and Occupational Health\, Fa
 culty of Medicine\, 9I���������). A significant proportion of research seeks to
  discover causes – causes of disease\, of disparities\, of longevity. Caus
 ation has been considered by philosophers\, religious scholars\, mathemati
 cians\, 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 gu
 ide data analyses that can help to understand whether observed relationshi
 ps 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 statistician
 s to design valid analyses.\n\n \n\n \n
DTSTART:20181206T230000Z
DTEND:20181207T000000Z
LOCATION:Auditorium\, Redpath Museum\, CA\, QC\, Montreal\, H3A 0C4\, 859 r
 ue Sherbrooke Ouest
SUMMARY:Cutting Edge Lecture in Science: Did this make that happen? Causati
 on\, causality\, and the statistician
URL:/redpath/channels/event/cutting-edge-lecture-scien
 ce-did-make-happen-causation-causality-and-statistician-287622
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