An Introduction to R
The following links take you to a full introductory course in R - an open source statistics package. Please take a moment to peruse this page before clicking on any links. The videos are hosted on youtube but can only be accessed through this webpage for now. Later, I intend to make them freely available to everyone - once I sort out all the glitches.
There will be a complete set of videos uploaded over the next few weeks. During this time, I intend to test certain videos and exercises. If you have any comments or constructive criticism, please send me them directly via email (see my GMU page for details).
Welcome to an comprehensive R course
The following course is free to all who wish to learn R. I provide reading assignments, youtube videos, and exercises throughout the course. Based upon my 10 years of teaching R Summer School, I devised a course that requires students to:
- Read assigned materials ahead of lecture
- Demonstrate a passing familiarity with the assigned readings
- Watch simple demonstrations of simple R programming techniques
- Complete exercises that enable students to master the materials
- Review exercise results
These five steps ought to produce competent R users in the shortest time. Students located in and around George Mason University’s Fairfax campus can get directed supervision from me during the course. I welcome everyone to try the course and send (Patrick McKnight) feedback as you see fit. Hopefully, you find this tutorial helpful.
Getting Started
- Why learn R?
- Watch this video: I provide several reasons to learn R.
- Additional Reading
- Exercise - install R
- Installing R - No video, just follow the following instructions for Windows, Mac OSX, or Linux (Ubuntu)
- Installing an editor - R works best with an editor and not just the use of the R command line or R terminal (for windows). You ought to consider using one of the many popular editors found here.