Week 9

SVD and Applications: Multiple Correspondence Analysis

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

During session I (Monday 16th, afternoon), each team will have 5 minutes to present their results from Homework I and 5 minutes to answer question(s).

Each team will have to prepare one or two slides and a short pitch commenting the pictures.

All team members must attend the defense and be prepared to answer questions.

Team Schedule
ls-leon 16:00
LOR75 16:10
abdjin-xxx 16:20
Sidi-xxx 16:30
MA7BY020-2026 16:40
sabrina-xxxx 16:50
Steven-xxx 17:00
T1S2G3 17:10
aya-xxx 17:20
sevikri-xxx 17:30
OsKaR31415 17:40
yaniogl 17:50

Bring your laptop with a working HDMI connector

Blackboard

Labs

  • Lab 10 Multiple Correspondence Analysis as 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 Principal Component Analysis as an application of SVD
  • Lab 9 Correspondence Analysis as an application of extended SVD

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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