Importance of statistical programming.
Programming languages help in facilitating the interaction of the hardware and the software. For instance, in artificial intelligence, languages such as python and Arduino are helpful in instructing the hardware, hence making robots mimic human behavior (Zhu & Kuo, 2017). In that sense, statistical programming languages are essential to the data scientist since they help to implement the statistical knowledge base to machines hence simplifying the complexity of solving analytical problems.
The advantage of r programming is that it is an open-source programming language meaning it has the advantage of having multiple libraries developed and maintained by a large community of experts (Braun & Murdoch, 2018). Also, it has numerous packages, which are efficient in solving data analysis problems, and finally, the programming language is platform-independent; hence, it can run in any platform, which is a disadvantage to the data science community.
However, the languages have a number of limitations, which include consuming large memory since it stores objects in physical memory. In my opinion, I think r-programming language is a superior language to others since it has the ability to operate on multiple platforms, and at the same time, it has a wide variety of efficient packages (Braun & Murdoch, 2018).
References
Braun, W. J., & Murdoch, D. J. (2016). A first course in statistical programming with R. Cambridge University Press.
Zhu, X., & Kuo, W. (2014). Importance measures in reliability and mathematical programming. Annals of Operations Research, 212(1), 241-267.