Programming tool created by Statisticians
Every industry has realized that the key to success is being capable of storing, analysing and analyzing data at a faster rate than their competitors. This big data revolution has resulted in a rise in demand for data scientists who can use Hadoop, and Python programming.
R, which is powered by machine learning and big data analytics, is an effective statistical tool for data scientists to extract answers from large data sets. R programming makes statistical analysis of data faster and more powerful than any other statistical computing tool.
R language has been used by over 2 million statisticians and Data scientists around the globe. With the widespread adoption of R language in business applications, its usage is growing exponentially. R programming language was originally developed for statistical analysis on a small scale in academic settings. The R programming language is a powerful tool for statistical computing . It can be used to visualize data, explore large data sets, and create new statistical models.
R is about drawing, not building. R is not part of Google’s page ranking or Facebook’s friend suggestion algorithm. Engineers will create prototypes in R and then give the model to Java or Python. Michael Driscoll is CEO of Metamarkets.
R has been a popular business analytics tool for over 20 years. Contributions from statisticians and the open-source community have helped to make R more powerful. R language is one of the most popular and powerful data science tools, as it offers different options to users. R programming language was created in 1997 to replace expensive statistical programming tools such as Matlab or SAS.
R is the first programming language to accept input via a command line. Although this might seem daunting to beginners, they can call pre-defined software packages with ready-made commands to perform data visualization or statistical analysis. Beginners can adapt pre-made R packages to learn R programming . R software packages are a bridge between the worlds of code experts and the simplicity of black-box commercial solutions.
