The demand for skilled data science practitioners in industry, academia, and government is rapidly growing and the R programming language is a key skill set for this kind of analysis and reporting. If you’re reading this, you probably already know that R is a free programming language for graphical and statistical analysis. This is the first in a series of blog posts I authored to teach you about how to use R. This first post explains where to find and use free R training solutions, and how to complete a simple analysis in R.
A Great Free Training Resource: edX Data Science Courses
edX is a nonprofit organization and massive open online course (MOOC) solution provider, with over 70 schools participating. One of the schools involved is Harvard University, and the institution is currently offering a Data Science series where you can gain the necessary knowledge base and skills to tackle real-world data analysis challenges for a very reasonable cost and pursue a certificate.
During the course, the professor covers concepts such as statistical models, probability, inference, regression and machine learning and teaches content to help develop skill sets such as R programming; data wrangling with dplyr; data visualization with ggplot2; basics of Linux file management; version control using GitHub; and working with RStudio.
Now that you know where to find free courses, I also wanted to help you get started with some key concepts to prepare you to learn more! The first step is to install R.
R can be downloaded for free from the Comprehensive R Archive Network (CRAN). I will show you how to install R for Windows. The installation is straightforward, but if you need additional help, please try one of the following resources:
Next, find the “R-3.5.1-win.exe Download Executable” on your computer and double-click the “R-3.5.1-win.exe file” to begin the installation. If you see a pop-up with an “Open File-Security Warning,” Click “Run.” Then, select your language and click “OK.”
Accept the “GNU Public License” on the next window by scrolling and clicking “Next;” then, select the installation location and click “Next” again:
On the next screen, accept the defaults and click “Next” again:
On the following screen, we do not need a custom startup, so select “No” and “Next.”
Use the Folder “R” for the program shortcut (change if you like something else), and click “Next.”
The next view will ask you to “Create a desktop shortcut” if you like; then click “Next” yet again.
Installation will now begin.
Initializing the R Console
To start the R Console, double-click your new desktop icon:
When we start RGUI, we see the R Console:
Let’s write our first R script. Let’s calculate the tip in U.S. dollars on a restaurant meal costing $22.16 if we give a 20% tip for great service. Our tip is $4.43 and our total to leave the server is $26.59.
Additional blog posts on more complex R concepts to follow; please contact firstname.lastname@example.org if you have any questions or need further help!