Why Learn R?

Practical reasons R is worth learning:

• Data analysis and statistics — R is a standard tool for statisticians, data scientists, and researchers in fields from medicine and biology to economics, psychology, and ecology.
• The tidyverse — a family of packages (dplyr, ggplot2, tidyr, and more) that makes cleaning, transforming, and charting data remarkably readable.
• Reproducible research — with Quarto or R Markdown, one document contains your text, code, results, and charts, and regenerates everything when the data changes.
• Cutting-edge methods — new statistical techniques often appear as R packages first.
• Interactive apps — Shiny turns an analysis into a web app without writing HTML or JavaScript.

Trade-offs worth knowing up front: R is a specialized language. For building websites, mobile apps, or general software, other languages fit better, and for deep learning and production machine-learning systems, Python has the larger ecosystem. R's syntax also has quirks that surprise programmers coming from other languages — this course points them out as they come up.