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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Model selection\, model frames\, and scientific in
 terpretation - Julia Brettschneider (University of
  Warwick)
DTSTART;TZID=Europe/London:20180308T094500
DTEND;TZID=Europe/London:20180308T103000
UID:TALK102037AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/102037
DESCRIPTION:Modelling complex systems in engineering\, science
  or social science involves selection of measureme
 nts on many levels including observability (determ
 ined e.g. by technical equipment\, cost\, confiden
 tiality\, existing records) and need for  interpre
 tability. Among the initially selected variables\,
  the frequency and quality of observation may be a
 ltered by censoring and sampling biases.   A model
  is\, by definition\, a simplification\, and the q
 uestion one asks is often not whether a certain ef
 fect exists\, but whether it matters. This crucial
 ly depends on the research objective or perspectiv
 e. Biased conclusions occur when the research ques
 tion is interwoven with the mechanisms in which th
 e variables for the analysis are selected or weigh
 ted.   Such effects can occur in any applications 
 that involve observational data. I will give some 
 examples from a few of my own research projects in
 volving quality assessment\, decision making\, fin
 ancial trading\, genomics and microscopy.
LOCATION:Seminar Room 1\, Newton Institute
CONTACT:INI IT
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