Setting up R and auxiliary programs for operating R and introducing a few tools if you get stuck.
Getting to know R
Excerpt from r-project
R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques and is highly extensible.
One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.
Many users think of R as a statistics system. We prefer to think of it as an environment within which statistical techniques are implemented. R can be extended (easily) via packages. There are about eight packages supplied with the R distribution and many more are available through the CRAN family of Internet sites covering a very wide range of modern statistics.
R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.
Getting to know RStudio
RStudio is an integrated development environment (IDE) for R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management.
What is the difference between R and RStudio?
Cran R (or simply R) is a programming language or a software environment as they call it for scientific computing and graphics and RStudio is an IDE for using R.
R and RStudio are not two different versions of the same thing. One can’t be substituted for the other. In fact, they work together. R is a programming language for statistical calculation. And RStudio is an Integrated Development Environment (IDE) that helps you develop programs in R. So if you want to learn more about them, you should start by learning R programming.
You can use R without using RStudio, but you can’t use RStudio without using R, so R comes first.
Now that this is clear, we continue with the installation:
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