images/# Installing R and R Studio on your Computer
What is R?
R is a free, open source, programming environment for statistical computing and graphics that compiles and runs on Linux, Windows and Mac OSX. It is a very capable programming environment for accomplishing everything from an introduction to data science to some of the most poweful, advanced, and state of the art computational and statistical methods. R is capable of working with big data, high dimension data, spatial data, temporal data, as well as data at pretty much any scale imaginable, from the cosmos to the quark and everywhere in between.
The statistical programming language R is often called an interpreted programming language, which is different from machine or native programming languages such a C or Java. An interpreted programming language is distinguished from machine languages because commands and arguments are interpreted prior to being executed by the programming engine. Python is another, closely related interpreted programming language that is also popular amongst data scientists. Although the use of an interpreter compromises speed, interpreted languages have a distinct advantage in their capacity to be more readily accessible and understandable. For example, commands such as plot, read.csv(), or cbind() can be fairly easily understood as the commands for plotting an object, importing a .csv file or binding together columns of data. This accessibility has led to the strength of an open source community that is constantly developing new functions for use within the R programming framework and well as supporting their use by the larger community. One of the major advantages of an open source approach to programming is the community that supports and contributes to R continued development.
In addition to being an open source programming framework, learning to use R also fullfills one of the fundamental principals of the scientific method, reproducibility. A reproducible programming environment functions by always keeping source data in its original state external from the R framework. Data is then imported to the work session and all changes occur within the framework through the code as it is sequentially executed. In this manner, any code one writes is perfectly reproducible not only an unlimited number of times you choose to run it as well as by any other person who has access to your code (unless you are incorporating probabilities type methods in your code). Compare this reproducible workflow concept to software that employs a graphic user interface (GUI), where commands are executed by selecting a pull down menu and following a series of preset options associated with each command. Excel, Pages, Arc or QGIS are examples of software that use a GUI as their primary means of user interaction. Most programming environments keep the code separate from the interpreter or compiler and is much more easily reproducible.
While R is easier to learn than more difficult programming languages such as C or Java, increasing its ease of use can be greatly advanced by using an integrated developer environment (IDE). One of the most popular IDEs for R is called RStudio. RStudio is dependent upon R in order to function, and literally sends commands and receives results to/from the interpreter. RStudio has a number of different features that facilitate programming, project management, graphics production, reviewing data and a whole slew of other useful functions. First you will want to install R and the associated tools, then follow by installing RStudio on your computer.
Installing R
Before installing R on your operating system, it is a good idea to briefly assess the state of your computer and its constituent hardware as well as the state of your operating system. Prior to installing a new software environment, such as R, I always recommend the following.
- Do your best to equip your personal computer with the latest release of your operating system
- Make sure you have installed all essential updates for your operating system
- Restart your computer
- Make sure that all non essential processes have not automatically opened at login, such as e-mail, messaging systems, internet browsers or any other software
After you have updated your computer and done your best to preserve all computational power for the installation process, go the R Project for Statistical Computing website.
Find the download link and click on it. If this is the first time you have downloaded R, then it is likely that you will also need to select a CRAN mirror, from which you will download your file. Choose one of the mirrors from within the USA, preferable a server that is relatively close to your current location. I typically select, Duke, Carnegie Mellon or Oak Ridge National Laboratory. A more comprehensive install of R on a Mac OS X will include the following steps.
- Click on the
R.pkgfile to download the latest release. Following the steps and install R on your computer. - Click on the XQuartz link and download the latest release of
XQuartz.dmg. It is recommended to update your XQuartz system each time you install or update R. - Click on the tools link and download the latest
clang.pkgandgfortran.pkg. Install both.
Following are two video tutorials that will also assist you to install R on your personal computer. The first one is for installing R on a Mac, while the second video will guide you through the process on Windows.
Video tutorial of how to install R on a Mac
Video tutorial of how to install R on Windows
Installing RStudio
RStudio is an integrated developer environment that provides an optional front end, graphic user interface (GUI) that "sits on top" of the R statistical framework. In simple terms, RStudio will make your programming experience much easier, and is typically a good way for beginners to start off with a programmer langauge such as R. RStudio assists with coding, executing commands, saving plots and a number of other different functions. While the two are closely aligned in design and function, it is important to recognizing that RStudio is a separate program, which depends on R having first been installed.
To install RStudio go to the following webpage and download the appropriate installer for your operating system.