20210103 We will first need to have available to us the
computer software that interprets our programs that we write as
sentences in the R language. Usually we will install this software,
called the R Interpreter, on our own computer and instructions for
doing so are readily available on the Internet. The
https://www.r-project.orgR Project is a good place to
start. Most GNU/Linux distributions freely provide R packages from
their application stores and a commercial offering is available from
Microsoft who also provide direct access within SQL Server and through
Cortana Analytics on the Azure cloud. Now is a good time to install
R on your own computer if that is required.
The open source and freely available
https://www.rstudio.com software is
recommended as a modern integrated development environment
(IDE) for writing R programs. It can be installed on
common desktop computers or servers running GNU/Linux,
Microsoft/Windows, or Apple/MacOS.
A browser version of also allows a desktop to access R
running on a back-end cloud server. This version of runs on
a remote computer (e.g., a server in the cloud) and provides a
graphical interface presented within a web browser on our own
desktop. The interface is much the same as the desktop version but all
of the commands are run on the server rather than on our own
desktop. Such a setup is useful when we require a powerful server on
which to analyse very large datasets. We can then control the analyses
from our own desktop with the results sent from the server back to our
desktop whilst all the computation is performed on the server itself
which may be a considerably more powerful computer than our usually
less capable personal computers.
An alternative cloud server setup is to connect to a remote cloud
server using X2Go as a remote desktop protocol.