Workshop Introduction
What is R?
R defines itself as “a language and environment for statistical computing and graphics.” R is an extremely important tool for data scientists.
History of R
R was first created by Ross Ihaka and Robert Gentleman to teach statistics at the University of Auckland. It was based on the S programming language, another statistical programming language. S was released as proprietary software, requiring users to pay for access. Martin Mächler convinced Ihaka and Gentleman to make R free and open source, and in 1997 they did just that, becoming a part of the GNU project.
Why Learn R?
- R code is great for reproducibility. You will still be able to run your code 10 years down the line.
- R is interdisciplinary and extensible.
- R works on data of all shapes and sizes.
- R produces high-quality graphics.
- R has a large, welcoming, and growing community
- R is free, open-source, and cross-platform!
Applications of R
R can be used in many data science related topics, such as:
- Statistical analysis
- Data mining
- Machine learning
- Data visualization
What is RStudio?
RStudio is the most popular IDE (integrated development environment) for R.
- An IDE is a text editor that also provides tools to make programming easier.
RStudio will make it easier to write and interact with our R programs. It provides many features, including the ability to visualize plots and inspect variables.
RStudio requires R to be installed for it to work. Make sure you have followed the steps outlined in the preparation page.