Most of us would acknowledge that getting up to speed with R involves a pretty steep learning curve - but it's worth every drop of sweat we shed in the process!
If you're learning basic statistics/econometrics, and learning R at the same time, then the challenge is two-fold. So, anything that will make this feasible (easy?) for students and instructors alike deserves to be taken very seriously.
Enter swirl - "statistics with interactive R learning" - developed at the Department of Biostatistics, Johns Hopkins University. It's dead easy to download and install swirl - it just takes a few moments, and you're underway.
There are simple, interactive, lessons that introduce you to the essential concepts, and you have the option to watch related videos. If you need to take a break part way through a lesson then you can save what you've completed, and pick up from that point at a later time.
My guess is that students will find swirl appealing and very helpful.
© 2013, David E. Giles
I think this might be of your interest, giving it is very related to a post of yours about parallel computing in RReplyDelete
The "rtools" package is required which is not available for the latest R version.ReplyDelete
Rtools is not required to install the swirl package. When you load the devtools package (which is required to download swirl directly from github) it will say you need Rtools, but that only applies if you intend on using devtools to build your own packages on a Windows machine. You can safely ignore this warning and proceed with the installation per the instructions here: http://ncarchedi.github.io/swirl/students.htmlDelete
Thank you for your kind words about swirl. We are working hard to improve the software.
I believe that swirl has the potential to become the de facto tool for teaching/learning R and statistics interactively. I've recruited some very talented people to help me develop the next iteration of the software.
My intention is for the R community to rally around (and take ownership of) this project. If anyone is interested in getting involved by contributing content or code, they should send me an email at firstname.lastname@example.org.
Thanks again and we look forward to contributing a valuable educational tool to the R and stats communities.
Nick - you're welcome. Congratulations on creating such a useful tool. I think we'll all be following further developments with great interest.Delete
A note from Mr. Nitpicker: a "steep learning curve" is a *good* thing. It means knowledge increases very quickly as a function of time. Why people insist on confusing the shape of a curve with its meaning is beyond me, but then again they probably think "literally" literally means "figuratively."ReplyDelete