Installing R on Ubuntu 15.10

R is a programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing.The R language is widely used among statisticians and data miners for developing statistical software and data analysis Polls, surveys of data miners, and studies of scholarly literature databases show that R's popularity has increased substantially in recent years.

R is an implementation of the S programming language combined with lexical scoping semantics inspired by Scheme.S was created by John Chambers while at Bell Labs. There are some important differences, but much of the code written for S runs unaltered.

Installing R Programming Language
You can install R by executing:
apt-get -y install r-base
Try running the command 'R' (capital letter).
R version 3.2.2 (2015-08-14) -- "Fire Safety"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
 q(save = "no")
Installing packages
R packages are packages that extend the capabilities of R. Enter R:
There are two ways to install R packages. First of all, if you want to install a package only for the current user, you can execute the following in R:
If you want to install a package available for all users on the system, there are multiple mirrors for both R and its packages. Execute:
su - -c "R -e \"install.packages('name', repos = '')\""
Replace name with the package name.
Please note: that you do not want to install R with packages on a server with less than 1 GB RAM.
For further learning, please visit the R website.

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