Going through the four previous posts, we hope that you now have a better view of what R, a powerful language for statistical computing and graphic, has to offer in our world of information. That is
– significant reduction of working time year after year for both statisticians and scientists,
– versatile capabilities to address all types of data: text, images, videos, sounds, and
– agility to adapt to any business and context: finance, political sciences, natural sciences,
All reducing drastically the risk of error which can lead to dramatic consequences.
In addition to the above let us see how R brings a source of innovation through its functioning and its community. It is difficult to disassociate these two. The wide community around R is the reason why its functionalities are under constant development. Many R packages and functionalities find their genesis in an idea or a need born in users’ minds, who then work on the development of these packages, often on a voluntary basis. Subsequently, other members of the R community contribute to the build by testing, commenting, improving or completing the packages, through add-ins, applications and functionalities.
It is through this participative and Open Source (OS) functioning that R is expanding every day with more and more powerful, varied and adaptive tools. R is like a Swiss army knife into which each user can incorporate new tools or functions in accordance with their needs and desires.
The impact of the R community on its software development is not limited to the technological development of the tool. The network of R users continues to grow thanks to the many conferences organized around the world, and this has the merit of targeting all socio-demographic and professional profiles. The number of R users is also increasing. These users return to their community and promote R through multiple and varied training, given in various formats and platforms, often voluntarily by R enthusiasts.
The multiplication of followers and users of R undoubtedly causes increased expectations concerning its functionality. We can expect that from these needs will flourish new R-tools, and still more specific innovations. The aRt of innovation!
This blog has been co-authored by Paul Majerus and Kamel Abid.
Paul Majerus is a Data analyst – Statistician at Sogeti Luxembourg.
About Alexandre Poncin
Alexandre graduated from the Université Catholique de Louvain and obtained his PhD in the field of psychology at the Université du Luxembourg. More specifically, he acquired expertise in neurosciences, learning, numerical cognition, data management, development of experimental design and quantitative analyses.
More on Alexandre Poncin.