# Supplementary Material

On this page, I will post additional resources and supplementary material for the course.

## Resources for R

In this course, we will use R as the main computational tool. Below are some resources:

- R for Data Science by Grolemund and Wickham.
- Hands-On Programming with R by Grolemund.
- Jenny Bryan’s course on Data wrangling, exploration, and analysis with R
- In particular, I recommend the notes on The Many Flavours of R objects

- Mine Cetinkaya’s curated list of resources for R
- If you’re looking for a deep understanding of R, I recommend Hadley Wickham’s book Advanced R
- RStudio has several great cheatsheets on their website. In particular, I recommend:

## Other useful textbooks

Here is a list of other textbooks that provide further (or complementary) details to Johnson & Wichern.

- Rencher (1998).
*Multivariate Statistical Inference and Applications*. - Anderson (2003).
*An Introduction to Multivariate Statistical Analysis*. - Timm (2002).
*Applied Multivariate Analysis*. - Muirhead (1982).
*Aspects of Multivariate Statistical Theory*.- This one is a classic text, but it is much more advanced than the other textbooks.