Since its release in 1997, R has emerged as a popular tool for statistical analysis and research. The flexibility and extensibility of R are keys attributes that have driven its adoption. Some of the advantages of R are related to the command line interface (CLI) form in which it is used. However, this does add to the challenge of learning to use R. The goal of this course is to build familiarity with the basic R toolkit for statistical analysis and graphics. Specifically:
- Become comfortable using R to manage and manipulate data
- Become familiar with some of R's most commonly used statistical procedures
- Explore simple programming in R
- Develop good analytical practices including documenting analysis and data manipulation, and collaborating with others in the R user/learner community
Course topics include:
- Getting Started: Basic R
- Working with Qualitative Data
- Working with Quantitative Data
- Documenting Work
- Finding Help
- Working with Two Variables
- The Data Frame
- Importing Data
- Manipulating Data and Repetitive Tasks
- Multivariate Data
Dr. Eric Nord is the primary author of the materials for this course.
- Access to your own copy of R. Please make sure that you visit Statistical Software page for the latest information about R.
- RStudio is a very nice platform for using R that will run on Windows, Mac, and Linux. R studio adds many useful features to simplify using R. All the functions used in this class can be performed without RStudio, but I will be demonstrating their use within RStudio.
Other Books and Resources on R:
- Statistics: An introduction using R. 2005. Michael J. Crawley. Wiley and Sons. (This was useful enough to me when I began learning R that I bought a copy.).
- Using R for Introductory Statistics. 2004. John Verzani. Chapman & Hall/CRC. (An extension of SimpleR) https://www.crcpress.com. If I was going to require a text, this would be it.
Familiarity with basic statistics is assumed.