# M1 in Economics and Economics and Statistics, Toulouse School of Economics

## Applied multivariate data analysis - Big data analytics (2014-…, 15 hours)

### A few hints

• Worksheet 1, exercise 1, question 1:

### Practical information

Nothing for the moment…

#### Final exam

Nothing for the moment…

For this course, I will intensively use R programming language. If you do not feel confortable with R, I advise you to check out this material:
• these slides, especially lessons 1 to 4 and lesson 6;
• install the R package swirl (instructions for the installation of R, RStudio and swirl are provided below). The package can be loaded into R using:
library(swirl)
and a swirl teaching session is started using
swirl()
Choose the course "1: R Programming" and follows the instructions: you have 12 short interactive courses that will help you to be more familiar with R;
• (not mandatory) if you want to go further, you can enroll to this on-line course.

For this course, the following (CRAN) packages must be installed (if you want to use your own computer): boot, mlbench, rpart, ipred, class, randomForest, e1071, foreach, doMC (unix-like OS users only) or doParallel (Windows users only).
In addition, the package rmr2 developped by Revolution Analytics must also be installed. This is done by following the tutorial provided at this link (in English).

## How to install R?

R can be downloaded for free on the official repository website. I also advise you to install RStudio which is a simple graphical user interface for R which is very handy in many situations. Finally, packages can be installed either the menu "Tools/Install packages" in RStudio or directly the command line:
install.packages("swirl")
in an R console.