
handle: 10072/416287
The R Project for Statistical Computing provides a software environment that is freeware for statistical computing and graphics. R and all of its libraries, or packages, allow its users to undertake many statistical techniques that include data handling and manipulation, classical statistical tests/analyses, Bayesian analyses, data reduction techniques, and cutting-edge statistics. The most common method of using R is through R Studio, an integrated development environment for R. R Studio includes a console, syntax-highlighting editor, code completion, smart indentation, tools for plotting, history, debugging, and workspace management, including package installation and updates. The R Project for Statistical Computing is often not considered an easy software program to learn, particularly if the user has little or no experience working with code or syntax in other statistical software. ; No Full Text
Statistical data science
Statistical data science
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
