The Evolution of R: From S-Inspired Language to Statistical Powerhouse

The Beginner’s Guide to the History of R Programming:

R Programming is basically the dialect of S Programming.

S History:

The S programming language was first developed in the late 1970s by John Chambers and his colleagues at Bell Laboratories. It was initially used for data analysis and graphics, and it served as the basis for the commercial software package S-PLUS, which was released in the early 1990s.

While S-PLUS was popular in the statistical community for many years, it has since been largely replaced by the open-source software environment R, which was inspired by S and developed by some of the same people who worked on S-PLUS.

As for the current version of S, it's not as widely used as R, and there are several different implementations of the S language that are still available today, including:

• S-PLUS: This is the commercial implementation of S that was developed by TIBCO Software Inc. It is still in use today, although it has been largely supplanted by R in the statistical community.
• OpenS: This is an open-source implementation of the S language that was developed by members of the R community. It is available under the GPL license and can be downloaded from CRAN (https://cran.r-project.org/web/packages/OpenS/index.html).
• R's S compatibility mode: R includes a compatibility mode that allows users to run S code within R. This feature was added to R in version 3.4.0 (released in 2017) and is designed to make it easier for users who are transitioning from S to R.

Overall, while the S programming language is no longer as widely used as it once was, its legacy can be seen in the continued use of S-PLUS and in R's compatibility mode.

R History:

R is a programming language and open-source software environment widely used for statistical computing, graphics, and data analysis. It was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, in the mid-1990s. R was initially developed as a free alternative to the commercial software S-Plus, which was popular in the statistical community at the time.

Since its creation, R has grown in popularity and is now one of the most widely used programming languages for data science and statistical analysis. It has a large and active community of developers and users who contribute to its development, support, and documentation.

R is licensed under the GNU General Public License and is available for free download and use from the Comprehensive R Archive Network (CRAN). R also has a number of integrated development environments (IDEs) available, including R Studio, which is a popular choice among R users.

R has a wide range of built-in statistical and graphical functions, and it also supports the use of packages, which can be downloaded from CRAN or other sources. These packages extend R's capabilities and allow users to perform more specialized or complex analyses. There are currently over 18,000 packages available on CRAN alone, covering topics such as machine learning, time series analysis, spatial statistics, and more.

One of the advantages of R is its flexibility and extensibility. Users can easily create custom functions and packages, making it easy to adapt to new research questions or analysis needs. Additionally, R has a robust graphics system that allows for the creation of high-quality visualizations, which are essential for effective communication of results.

Overall, R has become an essential tool for data scientists, statisticians, and researchers across a wide range of fields. Its popularity is due in large part to its flexibility, extensibility, and the large and active community of developers and users who contribute to its ongoing development and support.

Current Version Of R:

The current version of R as of my knowledge cutoff date (September 2021) is R 4.1.1, which was released on July 26, 2021.

R releases new versions on a regular basis, with major releases occurring every year or two, and minor releases (which include bug fixes and small improvements) occurring more frequently. The latest version can always be downloaded from the R Project website (https://www.r-project.org/).

One of the strengths of R is its active development community, which is constantly working to improve and extend the language. This community contributes new packages to CRAN (the Comprehensive R Archive Network), which provides a repository of more than 18,000 R packages that can be easily installed and used with R.

Users are encouraged to keep their installations of R up-to-date to take advantage of the latest features and bug fixes. The R community provides tools to make it easy to upgrade to the latest version, and many users rely on these tools to keep their installations current.

Useful Resources to Learn R:

To learn more about R, the following links may be useful: 

R Project website: https://www.r-project.org/
CRAN: https://cran.r-project.org/
R Studio: https://rstudio.com/
R Programming Wikibook: https://en.wikibooks.org/wiki/R_Programming
R for Data Science book: https://r4ds.had.co.nz/
Advanced R book: https://adv-r.hadley.nz/