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UID:20250917T220449EDT-1349wjVGOO@132.216.98.100
DTSTAMP:20250918T020449Z
DESCRIPTION:Title: Introduction to Statistical Network Analysis\n\n\n	Abstra
 ct:\n\n\nClassical statistics often makes assumptions about conditional in
 dependence in order to fit models but in the modern world connectivity is 
 key. Nowadays we need to account for many dependencies and sometimes the a
 ssociations and dependencies themselves are the key items of interest e.g.
  how do we predict conflict between countries\, how can we use friendships
  between school children to choose the best groups for study tips/help\, h
 ow does the pattern of needle-sharing among partners correlate to HIV tran
 smission and where interventions can best be made. Basically any type of s
 tudy where we are interested in connections or associations between pairs 
 of actors\, be they people\, companies\, countries or anything else\, we a
 re looking at a network analysis. The methods falling under this area are 
 collectively known as “Statistical Network Analysis” or sometimes “Social 
 Network Analysis” (which can be a bit misleading as we are not only talkin
 g about Facebook and the like). This workshop will give a general introduc
 tion to networks\, their visualisation\, summary measures and statistical 
 models that can be used to analyse them. The practical component will be i
 n R and attendees will get the most benefit if they are able to bring a la
 ptop along to work through examples.\n\n\n	Speaker\n\n\nNema Dean is a Seni
 or Lecturer of Statistics in the School of Mathematicss and Statistics at 
 the University of Glasgow. Her research interests are in developing new cl
 ustering and classification methods. Past work has involved research on fi
 nite mixture model based methods and variations that incorporate variable 
 selection and semi-supervised updating. Currently she is working on creati
 ng hybrid clustering methods using both parametric and classical algorithm
 ic approaches. She have also developed new mixture model clustering method
 s for discrete and space-restricted data.\n
DTSTART:20190329T170000Z
DTEND:20190329T203000Z
LOCATION:Room 521\, McIntyre Medical Building\, CA\, QC\, Montreal\, H3G 1Y
 6\, 3655 promenade Sir William Osler
SUMMARY:Nema Dean (University of Glasgow)
URL:/mathstat/channels/event/nema-dean-university-glas
 gow-295744
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