Introduction to R

The workshop is designed around my own idea of what a common data analysis workflow would entail: get -> clean -> explore -> visualize -> analyze -> repeat.

I hope...

Prior to the start of the workshop everyone will need to have had the software installed and tested. You will need to have the following installed (links assume Windows as...

Over the course of the next two days we are going to walk through a typical data analysis workflow in R. But, with this first lesson we are going to...

The second lesson is going to start to lay the foundation for working with data in R. We will cover some of the very basics of R first, then move...

In this third lesson we are going to start working on maninpulating and cleaning up our data frames. We are spending some time on this because, in my experience, most...

Our next three lessons (Explore, Analyze, and Visualize) don’t actually split neatly into groups. That being said, I will try my best, but there will be overlap. For this lesson...

The focus of this workshop hasn’t really been statistics, its been more about R, the language. But, it is pretty much impossible to talk a lot about R without getting...

The second section will run through a fairly quick example of using a package, randomForest for some analysis. I’ve included this section just to show how (relatively) trivial it...

One of the frequently touted strong points of R is data visualization. We saw some of that with our use of base graphics, but those plots were, frankly, a bit...

In theory, you now have a basic understanding of how to conduct a typical data analysis workflow in R. All that is left is to be able to write it...

Having now presented these materials to multiple groups of eager USEPA students, I wanted to add one last post to the site with some parting thoughts. But before I do...