EC
Advanced statistics
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/