Week 8

SVD and Applications

Important

• Session I Sophie Germain (2017) Monday 16h-17h30
• Session II Sophie Germain (2011) Friday 16h45-18h15
• Calendar

Correspondence Analysis

Labs

• Lab 9 Correspondence Analysis as an application of SVD

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

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

• Bin Yu and Rebecca Barter, Veridical Data Science
• R for data science
• Advanced R
  • S3 classes
  • S4 classes
• Greenacre M. Correspondence Analysis in Practice. 2nd edn. 2007. Chapman & Hall/CRC, London. Published in Spanish as La Practica del Análisis de Correspondencias, Fundacion BBVA, Madrid; 2008.

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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