R is a programming language and free software environment for statistical computing and graphics, developed by Ross Ihaka and Robert Gentleman in 1993. The R language is widely used among data miners and statisticians for developing statistical software and data analysis.
It includes machine learning algorithms, linear regression, time series, statistical inference to name a few. Most of the libraries are written in R, but for the heavy computational task, C codes are preferred. R is not only preferred by academics, but many large companies also use R programming language, including Facebook, Google Uber and so on.
Data analysis with R is done in a sequence of steps;
Program: R is a clear and accessible programming tool.
Transform: R is made up of a collection of libraries specially designed for data science.
Discover: This involves investigation of the data, refine your hypothesis and analyze them.
Model: R provides a wide range of tools to conquer the right model for your data.
Communicate: Integrate codes, graphs, and outputs to a report with R markdown or create shiny apps to share with the world.
R is used for Statistical inference, data analysis, and machine learning algorithms. It is used in the healthcare industry and academics.
Easy guide to R Programming
Detail analysis like clustering, correlation, and data reduction are done with R.
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