What is R Programming?

Programming is a field that invites and sees innovation and inventiveness every day having varied uses in developing almost every application, from gaming, to websites, to even shopping apps and social media we use daily. Every language used in programming has its own speciality, like JavaScript for making pages interactive, Python for artificial intelligence programming and more.

Among this plethora of programming languages, lies a language that is only known by a letter and it is called the R programming language. Let us find out more about this language, it’s developments and its uses in today’s programming!

Developed in 1991 by Ross Ihaka and Robert Gentlemen in New Zealand, it is an alternate implementation of the basic S language that was developed in Bell Labs in 1976. The name of this programming language is a play on the names of the developers and partly on the programming language it was inspired by, S. In 1995, the developers made this programming language available as an open source software under GNU General Public Licence.

R is a programming language that is proficient for statistical computing and graphics. It provides a wide and highly extensible array of statistical techniques like linear and non-linear modelling, time series analysis, classification, clustering and other graphical techniques. R language proves to be a highly efficient openly available substitute for the top choice language for statistical methodology which is the S language.

R programming language’s strength lies in the many features it provides to a developers and researchers-

  • Production of well-designed publication worthy plots with the correct mathematical formulae and symbol representation.

Like every other language for programming there is, this one too comes with some issues. The disadvantages of R programming language includes its speed, which is less when compared to other languages like Python or MATLAB, it may use up all the available memory to run. However the features and applications of this programming script outweighs these problems by a lot.

R’s vast repository of features make it capable of carrying out basic statistics like finding the measures of central tendencies (mean, median and mode), and finding probability distributions using Chi-Squared distribution, normal distribution or bi-nomial distribution. With such a varied level of usefulness R programming language truly integrates into all fields including programming, science, finance and more!

Now that we know more about R programming language, it is easy to understand why this language is crucial for data analysis and visualization. This programming language is a must learn for anyone who wishes to foray into the field of data science and similarly into statistics to view the surprises held by it and to understand how it makes a truly efficient system for data prediction and more!



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