M1 S&E - Big data analytics

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

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

Material

A few hints

  • Worksheet 1, exercise 1, question 1:

Practical information

At this link, you can find the project group to which you are associated.

  • Project 1 (exercise 3, questions 1-3) is affected to groups 3, 5, 10 and 11. It has to be sent back to me by e-mail before Tuesday February, 20th, 8 pm. Make sure that I properly received your work.
  • Project 2 (exercise 2, end of question 2) is affected to groups 4, 6, 8 and 9. It has to be sent back to me by e-mail before Wednesday February, 28th, 12 am. Make sure that I properly received your work.
  • Project 3 (exercise 1, questions 9 and 10) is affected to groups 1, 2 and 7. It has to be sent back to me by e-mail before Tuesday March, 20th, 12 am. Make sure that I properly received your work.

Final exam

The final exam will be held on April 4th, 1.30-4.30 pm. The exam will be related to the practical part of this work. All documents will be allowed as well as use to documents on the internet. However, any kind of communication with another person during the exam is strictly forbidden. Any attempt to cheat will be severely penalized.

exam and its correction

About R

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.