A beginner’s guide to learning the statistical programming language R
Published in · 3 min read · Jan 20, 2021
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I created a mini-course on R a couple of years ago and decided to incorporate the main ideas into a blog to reach more people trying to learn R. While I do most of my work in Python, you can’t beat R’s statistical packages and visualizations through ggplot2 (more on this later).
R is an open-source (free!) software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS, making it an ideal platform for all your statistical computing needs. R is frequently used by data scientists, statisticians, and researchers.
Next to python, R is the most popular language in data science and R has become the standard language for statistical computation. R has a learning curve, but once you learn the foundations, it is incredibly easy to use it for a variety of projects. There are a number of libraries in R that make doing complex statistical calculations and impressive visualizations easy. You can also use R to make web apps with the R Shiny package! R is incredibly versatile, and when paired with R Studio, it becomes the ideal environment to learn about…
