I am working and auditing this course online, so I archived my work so I can revise it again later what I have done up to date.
To install R in your system:
The R code which Rafa runs in this video is available here:
After installing R on System, run the command
> install.packages("swirl")
Then, select the location of the server to download (e.g. Australia [Perth], etc).
> library(swirl)
Using this command is depicted a selection on using a swirl library on the workspace.
You can go through the examples and exercises on how to use the command in the swirl packages.
If you have done work in your workspace before, the program will ask you to remove things from your workspace by using command > rm(list=ls())
Then type > swirl() to begin
You
can download the individual Rmd scripts from Github by clicking on the
filename, and then the 'Raw' button. Save this file to your computer,
and then open it in RStudio.
Running Lab Code
All software used for the class is free and open source:
- R can be downloaded and installed from CRAN (Comprehensive R Archive Network). If possible download the latest release (R 3.3.0 released 3 May 2016).
- We recommend using RStudio, a slick visual interface for R.
After installing R on System, run the command
> install.packages("swirl")
Then, select the location of the server to download (e.g. Australia [Perth], etc).
> library(swirl)
Using this command is depicted a selection on using a swirl library on the workspace.
You can go through the examples and exercises on how to use the command in the swirl packages.
If you have done work in your workspace before, the program will ask you to remove things from your workspace by using command > rm(list=ls())
Then type > swirl() to begin
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