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DESCRIPTION:Overview\nHigh-Dimensional Statistics with R\n\nThis course is 
 intended for those who have a working knowledge of statistics and linear m
 odels with R and wish to learn high-dimensional statistical methods with R
 .\n\nThis is a short course aimed at familiarising learners with statistic
 al and computational methods for the extremely high-dimensional data commo
 nly found in biomedical and health sciences (e.g.\, gene expression\, DNA 
 methylation\, health records). These datasets can be challenging to approa
 ch\, as they often contain many more features than observations\, and it c
 an be difficult to distinguish meaningful patterns from natural underlying
  variability. To this end\, we will introduce and explain a range of metho
 ds and approaches to disentangle these patterns from natural variability. 
 After completion of this course\, learners will be able to understand\, ap
 ply\, and critically analyse a broad range of statistical methods. In part
 icular\, we focus on providing a strong grounding in high-dimensional regr
 ession\, dimensionality reduction\, and clustering.\n\nEd-DaSH\n\nEd-DaSH 
 is a Data Science training programme for Health and Biosciences. The team 
 has developed workshops using The Carpentries platform on the following to
 pics. See workshops for dates and registration details. All workshops will
  be delivered remotely.
SUMMARY:High-Dimensional Statistics with R
URL;VALUE=URI:https://edcarp.github.io/2022-07-26_ed-dash_high-dim-stats/
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