Week 12

TBA

Important
  • Session I Olympe de Gouges (130) Wednesday 13h30-15h
  • Session II Sophie Germain (2012) Friday 9h00-10h30
  • Calendar

Labs

We will work on coding and package development, with following goals

  • developping methods for tidy, glance, methods for S3 classes FactomineR::CA, FactomineR::MCA.
  • investigate problems posed by output of cancor
  • develop autoplot methods of FactomineR::CA, FactomineR::MCA
  • special emphasis on documentation and testing

We still rely on the previous labs

  • Lab 1 - Introduction to R and RStudio
  • Lab 2 - Introduction to Data Visualization using Gapminder dataset
  • Lab 3 - Working with dplyr
  • Lab 4 Univariate categorical variables
  • Lab 5 Univariate numeric variables
  • Lab 6 - Linear Regression I
  • Lab 6 - Linear Regression II
  • Lab 7 - Linear Regression II
  • Lab 8 Principal Component Analysis as an application of SVD
  • Lab 9 Correspondence Analysis as an application of extended SVD
  • Lab 10 Multiple Correspondence Analysis and Canonical Correspondence Analysis as applications of extended SVD
  • Lab 11 Clustering with \(k\)-means
  • Lab 12 Hierarchical clustering

Further work

Review the content of the two labs. Work out every part you do not already know. Report an issue if you are unhappy with the proposed solutions/hints.

Further reading

Logistics

: you will work with the R programming language in this course.

You need either to install R, RStudio and VS Code on your computer, or to use your posit-cloud account.

Install Quarto on your computer to render the .qmd files.

Please follow the instructions here to install R, RStudio, VS Code, and Quarto or to access posit-cloud.

Please activate your ENT account (follow the instructions on Moodle). You will be able to access the PostGres server.



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