R was invented by Ross Ihaka and Robert Gentleman in the year 1991 at the University of Auckland, New Zealand, as an implementation of the S language, a statistical language. R is widely used by data analysts and scientists in order to process and visualize data. Although it is mostly used for statistics, it is organized under the object-oriented programming model, like Python for example. In addition, it is open source and free unlike SAS, so packages can be downloaded in order to expand on its capabilities.
Tech Kits
Beginner
Introducing R Programming
Length: 30 - 60 Minutes
Description: R is a language and environment for statistical computing and graphics. It is both widely used and open-source, providing great flexibility for data analysis. This tech kit provides an overview of the R interface along with a number of examples involving arithmetic operations, variables, comparison operators, vectors, matrices, data frames and factors.
Intermediate
Exploring the Capabilities of R
Length: 30 - 60 Minutes
Description: R is not just a statistical platform for data cleaning, analysis, and representation. It simplifies data science projects by facilitating data wrangling, supporting data visualization, offering valuable R libraries, and streamlining machine learning efforts. In this tech kit, the user explores using packages, relational operators, conditional operators, loops, and functions within R to prove why it is so valuable.
Advanced
Recognizing the Versatility of R
Length: 30 - 60 Minutes
Description: Many useful R functions come in packages: free libraries of code written by R’s user community. In addition to built-in packages, over 5,000 packages are available for download. This tech kit explores importing, tidying, summarizing and visualizing data using built-in capabilities and additional packages.
Projects
Resources
R SDK
Type: Programming Language
Description: R is a language and environment for statistical computing and graphics.
RStudio 1.1.383
Type: Desktop Application
Description: 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