The project is for individuals in teams who are using, or planning to use, R to address problems in the data sciences. This assumes a first course in Data Carpentry or some similar introduction to working with data using computer tools. However, for those who have not had that, links to appropriate material will be provided along the way.
This is not fully laid out as a course, although it could be used as such. Much of the material has been tried out in various courses and training venues. There are many references out to course and research material of others so that teams can build on their experience. That, in fact, is how any science progresses. A web version is at http://www.stat.wisc.edu/~yandell/R_for_data_sciences. This material is being used in Fall 2017 for the COMBEE R Study Group at UW-Madison.
The syllabus provides the broad organization. Material is organized into verb folders roughly based on this syllabus.
- curate data structures
- visualize data relationships
- organize data methods and documentation
- analyze data with linear and other models
- profile code for efficiency and error checking
- connect with other data science tools beyond R
Other material in this directory:
| item | contents |
|---|---|
| overview | Overview of R Material |
| reference | list of references |
| repositories | list of data repositories |
| learnR | R Language Tips & Tricks |
| background | background material on R and data science |
| Bates | index of teaching material developed by Douglas Bates |
data |
folder with local data |
| LICENSE | fair use license |
Many people contributed to this material. Thanks to Douglas Bates for his coteaching and help in Fall 2014 and 2015. The COMBEE R Study Group kindly shared their study material, and are allowing me to use the R Study Group in Fall 2017 to test out this.
This and related pages come from https://github.com/datascience-uwmadison/R_for_data_sciences.