Introduction to Programming in R
Introduction to Programming in R
A gentle and practical introduction to data analysis in R for people with no programming background. Learn R programming concepts with a focus on preparing and analyzing data.
About This Course
This mini-course is aimed at people with no programming background that are looking for a gentle and practical introduction to data analysis in R. We cover how to read data into R, manipulate data with tools from the tidyverse package dplyr, and conduct statistical simulations.
Each module involves pre-recorded lectures with guided practice exercises and corresponding labs to practice the skills taught. The labs are an essential part of the learning process as they walkthrough the use of many key functions and topics not explicitly covered in the videos.
Additional Resources
- tidyverse cheatsheets - start with dplyr and ggplot
- R for Data Science - free online book with clear explanations of many tidyverse functions
Course Modules
Getting Started
Introduction to the course structure and setting up your R environment.
Introduction and Motivation for R Programming
Why R? Understanding the value of R for data analysis and statistical computing.
Installing Packages and Reading Data
Learn to extend R’s capabilities with packages and import data from various sources.
Vectors and Lists
Master fundamental data structures: vectors and lists for organizing data in R.
Data Manipulation
Essential techniques for cleaning, transforming, and reshaping your data using dplyr.
Data Manipulation and Analysis II
Advanced data manipulation techniques for complex analysis tasks.
Data Visualization as a Tool for Analysis
Create compelling visualizations with ggplot2 to explore and communicate your findings.
Grouped Analysis
Perform sophisticated group-wise operations and aggregations on your data.
Iteration
Automate repetitive tasks with loops and functional programming techniques.
Writing Functions
Create your own functions to make your code more reusable and maintainable.