R is an integrated suite of software facilities for data manipulation, calculation and graphical display. Among other things it has

• an effective data handling and storage facility,
• a suite of operators for calculations on arrays, in particular matrices,
• a large, coherent, integrated collection of intermediate tools for data analysis,
• graphical facilities for data analysis and display either directly at the computer or on hardcopy

The term “environment” is intended to characterize it as a fully planned and coherent system, rather than an incremental accretion of very specific and inflexible tools, as is frequently the case with other data analysis software.

R is very much a vehicle for newly developing methods of interactive data analysis. It has developed rapidly, and has been extended by a large collection of packages. However, most programs written in R are essentially ephemeral, written for a single piece of data analysis.

• Using R and RStudio https://www.amherst.edu/people/facstaff/nhorton/node/567498
• Using R Studio http://dss.princeton.edu/training/RStudio101.pdf
• R Studio https://www2.stat.duke.edu/courses/Spring14/sta101.001/UsersGuide.pdf
• Link to Stats Course Using R http://dss.princeton.edu/training/
• Comprehensive Manual https://cran.r-project.org/doc/manuals/r-release/R-intro.html
• Examples with Sample Data http://sas-and-r.blogspot.com/p/statistics-examples.html
• A Crash Course in R http://spatial.ly/2013/05/crash/

• Spatial data in R: Using R as a GIS
• R as a GIS: overlay, rgeos, osmar, networks http://geostat-course.org/system/files/rgis.pdf
• R Spatial Tips http://spatial.ly/r/