Introduction to Programming in R
A gentle and practical introduction to data analysis in R for people with no programming background. Each module includes pre-recorded lectures, guided practice exercises, and labs. We cover reading data into R, manipulating data with dplyr, and conducting statistical simulations.
Getting Started ·course structure, setting up your R environment view
Introduction and Motivation for R Programming ·why R, statistical computing, data analysis view
Installing Packages and Reading Data ·extending R, importing from various sources view
Vectors and Lists ·fundamental data structures in R view
Data Manipulation ·cleaning, transforming, reshaping with dplyr view
Data Manipulation and Analysis II ·advanced techniques for complex analysis tasks view
Data Visualization as a Tool for Analysis ·ggplot2, exploratory and communicative graphics view
Grouped Analysis ·group-wise operations and aggregations view
Iteration ·loops, functional programming, automation view
Writing Functions ·reusable code, maintainable analysis view
$ cat resources.txt
→ tidyverse cheatsheets — start with dplyr and ggplot2
→ R for Data Science — free online book covering most tidyverse functions