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High-Dimensional Data Analysis in Ecology and Evolutionary Biology Using R

28 May – 1 June 2018, Lund

This workshop is intended for researchers who have interest in analyzing high-dimensional data (many continuous variables or dissimilarity matrices from other types of data). The workshop introduces participants to linear model methods incorporating randomized residual permutation procedures, which allow analysis of high-dimensional data with high statistical power. Emphasis is placed on evaluation of linear model effects for high-dimensional data, how to calculate effect sizes, comparison of models, comparison of covariance structure, and the resampling methods that make these objectives possible. Participants will gain both an understanding of the cutting-edge non-parametric methods for analysis of high-dimensional data and tools for performing such analyses in R.

Teachers

  • Dean Adams
  • Mike Collyer
  • Johan Hollander
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