From ElateWiki




R itself can be described as a programming language that is used for statistical computing and analysis,graphics representation and reporting. R was created by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand. R was given its name from the first names of the two R authors. R is currently developed by the R Development Core Team. The stable beta version of R was released in 2000.


RStudio is a free and open-source integrated development environment for R. It was founded by JJ Allaire, who is also the creator of the programming language ColdFusion. RStudio is available in open source and commercial editions and runs on the desktop or a web browser that is connected to the RStudio Server. Work on RStudio started in December of 2010.


The R programming language contains libraries that allow for a wide variety of statistical and graphical techniques. Some of the techniques and models that can be used are linear and nonlinear modeling, classical statistical tests, time-series analysis, clustering, classification, and many others.

The capabilities of R are expanded through many user-created packages. Some of the packages are:

  • rmarkdown: A package that allows you to insert R code into a markdown document.
  • Shiny: Allows a user to easily build interactive web applications within R.
  • ggplot2: A package that contains enhanced data visualization tools to create multi-layered graphics.
  • dplyr: A package that focuses on the manipulation of data frames.

Corporate/Personal Usage

Data analytics and statistical analytics have experienced a large and continued growth of importance within businesses over time. Analytics using external or internal data allows a business or individual to identify trends or draw insights and recommendations to add efficiency to any internal or external business need. Research has shown that there will be a strong demand for individuals with in-depth analytical skills using open-source software such as RStudio. Some of the positions that will experience a growth in demand are data scientists, data analyst, business intelligence analyst, consumer insights, and many more.

SAS defines data scientist as a new breed of analytical data experts who have the technical skills to solve complex problems - and the curiosity to explore what problems need to be solved. Data scientists need to have a solid understanding of statistics and machine learning, as well as an understanding of coding languages such as SAS, R, or Python. Each of those languages are very similar in terms of the capabilities of each.

The area of data science or data analytics itself can help businesses achieve a competitive advantage over its competitors. It allows for data back decisions to be made when assessing business problems and also allow for room for innovation.



Looking at the screenshot above, you can see that there are four different windows that each contain different fields that allow for easier usage of R Studio.

  • The top left window is used for writing scripts of R code. This allows you to record the code that you are writing for the program to run and allows for editing of the code. Some examples of code are assigning values to variables, running statistical formulas that can be applied to specific columns or the entire dataset, as well as manipulate subsets of the data. Multiple scripts can be open at a time and can be saved just like a normal txt file.
  • The top right window contains the different values, datasets, lists, or any other variables that have been defined.
  • The bottom left window is the "Console", also known as the place where the running of the code takes place. It is like a command prompt and shows if the lines of R code are ran successfully or return an error.
  • The bottom right window servers as more of a menu prompt, and can display what packages are available for usage, and the plots that you can create and displays the visualizations created with the code.


When downloading R and R Studio, you must first have R downloaded first. This allows for you computer to have the language itself downloaded so that it can be used in the R Studio platform.

Windows Download

Mac Download

Once R is downloaded, you will then need to download the R Studio platform. R Studio Download

After R Studio is downloaded, you are then able to use the platform for data visualization, manipulation, and more. The video below will walk through a few simple commands that the platform is capable of.