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Description

  Acquire basic skills in multivariate statistics and know how to visualize and analyze High-dimensional data.

Compétences visées

  • Interpret and understand regression models
  • Understand the multiple testing problem and be familiar with the Bonferroni method and the Benjamini-Hochberg procedure
  • Understand the different features of the high dimension reduction techniques : Principal Component Analysis (PCA), Multidimensional Scaling (MDS), Stochastic Neighbour Embedding (SNE)
  • Understand clustering methods of High-dimensional data such as : K-means, Agglomerative clustering (dendogram)

Bibliographie

Susan Holmes, Wolfgang Huber. Modern Statistics for Modern Biology. http://web.stanford.edu/class/bios221/book/

Contact

Responsable(s) de l'enseignement
Nicodeme Paul : npaul@unistra.fr