This site is intended to be a resource for digital analysts who are interested in learning or expanding their knowledge of R and statistics. That’s from whence the semi-silly name came from:

Digital Analysts: R and staTISTICS


(Clearly, this is not a site about “branding an initiative” or “coming up with a totally awesome name for a site!”)

This site is developed and maintained by Mark Edmondson and Tim Wilson, with a semi-intentional assist from Donal Phipps and others. If you have feedback or suggestions for the site, hop over to GitHub and log an issue. (A GitHub account is required, but, if you’re using R, you should have one! And, creating one is quick and free if you don’t.)

Our hope is that, for the analyst who is new to R, by going through the resources on this site, the code and output below will start to make some real sense!

3-Day Training: Columbus, Ohio, US - June 13-15, 2017

See the class details for more information.


Some Examples for Inspiration

Below are a couple of examples of some uses of R with web analytics data. Check out the examples under the Examples dropdown for these examples and more, including the code used to generate them.

Visualizing Sessions in a Heatmap

This example shows a visualization of traffic to a site broken down by day of week and hour of day.

Forecasting with Holt-Winters

This example uses the Holt-Winters method to apply some smoothing and seasonality to the base data to build a forecast that includes the likely range of values.

These are just two of an infinite number of examples of what can be done with the power of R, a bit of knowledge of statistical concepts, and access to web analytics data. Happy coding!