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DTSTAMP:20260809T031922Z
UID:13ce610c-3fb0-4191-830c-d2d72b127854
DTSTART:20170613T123000Z
DTEND:20170614T210000Z
DESCRIPTION:Before we can begin to apply rigorous statistical tools to rese
 arch data\, we often need to approach our data intuitively\, and look for 
 meaningful associations\, surprising patterns\, or irregularities\, to for
 mulate hypotheses. This is Exploratory Data Analysis (EDA). This workshop 
 introduces the essential tools and strategies that are available for EDA t
 hrough the free statistical workbench R. Steps covered in this workshop ar
 e broadly relevant for many areas of modern\, quantitative biology such as
  flow cytometry\, expression profile analysis\, function prediction and mo
 re.\n\nParticipants will gain practical experience and skills to be able t
 o:\n\nUse R and its analysis tools\, read and modify code\, and explore pr
 otocols that can be adapted for their own research tasks.\nWrite R functio
 ns and analysis scripts.\nPlot and visualize data using the elementary bui
 lt-in routines via their (sometimes bewildering) array of parameters to so
 phisticated\, publication-ready presentations.
LOCATION:Toronto
SUMMARY:Exploratory Analysis of Biological Data using R
URL;VALUE=URI:https://bioinformatics.ca/workshops/2017/exploratory-analysis
 -biological-data-using-r-2017
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