Massive Data Analysis

Author
Affiliation

Martin Bari Garnier

Published

February 26, 2024

This work takes up what has been done in the course of practical work on the Massive Data Analysis teaching unit. Think of it more as tutorials than as complete guides to fully mastery the presented techniques.

Covered topics

The following topics are presented here in the chronological order in which they were studied. If you are new to all of them, please respect this order. All manipulations were done with the R programmation language.

Citation
citation()
To cite R in publications use:

  R Core Team (2023). _R: A Language and Environment for Statistical
  Computing_. R Foundation for Statistical Computing, Vienna, Austria.
  <https://www.R-project.org/>.

A BibTeX entry for LaTeX users is

  @Manual{,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2023},
    url = {https://www.R-project.org/},
  }

We have invested a lot of time and effort in creating R, please cite it
when using it for data analysis. See also 'citation("pkgname")' for
citing R packages.