Computing for Data Analysis by Roger D. Peng.
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment, discuss generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, creating informative data graphics, accessing R packages, creating R packages with documentation, writing R functions, debugging, and organizing and commenting R code. Topics in statistical data analysis and optimization will provide working examples.
- Software for Data Analysis by John M. Chambers (Springer). Errata/notes.
- S Programming by Brian D. Ripley and William N. Venables (Springer). Website for S Programming.
- Programming with Data by John M. Chambers (Springer). Website for Programming with Data
The volume by Chambers looks comprehensive (500 or so pages) enough to be sufficient for the course.
Next Session: 24 September 2012 (4 weeks)
Workload: 3-5 hours per week