Learning Statistics with R

In 2011, I (Dani) started teaching the introductory statistics class for psychology students offered at the University of Adelaide, using the R statistical package as the primary tool. I wrote my own lecture notes for the class, which have now expanded to the point of effectively being a book - it's still a work in progress, but it has reached a "first draft" stage. You can download the current version from this page, and you can purchase a copy from Lulu, a print-on-demand service, so that students can obtain hard copies at a much lower price than a traditional academic publisher would charge. The book is available here:

The book is associated with the lsr package, available on CRAN and github. The data sets analysed in the book can be downloaded here, and the source files for the book are here. The table of contents for the book is listed below, and some additional resources are linked to at the bottom of the page.

New! This project has been dormant for a while (I know, I know..), but I have at long last started the arduous process of extracting the LSR content from the awful LaTeX templates I used originally, and moving it into R Markdown. So far I haven't been able to put this together into a shiny new LSR version, but I've been using early version of it for an introductory programming class, available on the PSYR page.

I. Background

II. An introduction to R

III. Working with data

IV. Statistical theory

V. Statistical tools

VI. Other topics

Additional resources

Strictly speaking the book isn't linked to any particular lecture slides or exercises. However, I have on occasions run some brief one-day workshops at a few places, and it tends to loosely follow the book. The workshop consists of three parts, an introduction to the basic mechanics of R, followed by a fairly rapid overview of some core statistical tools in R, and some extra bits and pieces at the end: