Programming Tutorials

Excellent Free Tutorials to Learn R

The R language is the de facto standard among statisticians for the development of statistical software, and is widely used for statistical software development and data analysis. R is a modern dialect of S, one of several statistical programming languages designed at Bell Laboratories.

R is much more than a programming language. It’s an interactive suite of software facilities for data manipulation, calculation, and graphical display. R offers a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The ability to download and install R packages is a key factor which makes R an excellent language to learn. What else makes R awesome? Here’s a taster.

  • It’s free, open source, and available for every major platform. So anyone can repeat your work whatever platform they run.
  • A huge set of high quality packages for statistical modelling, machine learning, visualization, and importing and manipulating data.
  • Cutting edge tools.
  • A suite of operators for calculations on arrays, in particular matrices.
  • Deep-seated language support for data analysis. This includes features likes missing values, data frames, and subsetting.
  • Powerful tools for communicating your results.
  • Produce publication-quality graphs, including mathematical symbols. Dynamic and interactive graphics are available through additional packages. R packages make it easy to produce HTML or PDF, and create interactive websites with Shiny, a sublime R package.
  • A strong foundation in functional programming. The ideas of functional programming are well suited to solving many of the challenges of data analysis. R provides a powerful and flexible toolkit which allows you to write concise yet descriptive code.
  • RStudio, a powerful integrated development environment.
  • Powerful metaprogramming facilities; a fantastic environment for interactive data analysis.
  • Connects to high-performance programming languages like C, Fortran, and C++.
  • An amazingly vibrant and helpful community.

Packages are the fundamental units of reproducible R code. They include reusable R functions, the documentation that describes how to use them, and sample data. The CRAN package repository hosts over 15,000 packages, and Bioconductor is home to over 1,800 packages.

Here’s our recommended tutorials to learn R. If you’re looking for free R programming books, check here.

1. Introduction to R and RStudio for Data Science by LinuxLinks

This is a crash course in data science designed for the absolute beginner. Get up to speed in 20 minutes. It assumes only basic computer skills and no programming knowledge. If you’re interested in learning about data science, this is a great place to start.

Read the tutorial

2. Cookbook for R by Winston Chang

The goal of the cookbook is to provide solutions to common tasks and problems in analyzing data.

Read the tutorial

3. R Tutorial for Beginners: Learning R Programming by guru99

This is a complete course on R for beginners and covers basics to advance topics like machine learning algorithm, linear regression, time series, statistical inference etc.

Read the tutorial

4. Elementary Statistics with R by R Tutorial

The R solutions are short, self-contained and requires minimal R skill. Most of them are just a few lines in length.

Read the tutorial

5. R Tutorial by Kelly Black

These materials are designed to offer an introduction to the use of R. It is not exhaustive, but is designed to just provide the basics. It has been developed for students who are new to R but have had some basic experience working with computers.

Read the tutorial

6. R Programming Tutorials by thenewboston

A set of videos with good coverage.

Watch the video tutorials

7. 15 Page Tutorial for R by Study Trails

A 15 page example based tutorial that covers the basics of R.

These tutorials are designed for beginners in R, but they can also be used by experienced programmers as a refresher course or as reference.

Read the tutorial

All tutorials in this series:

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